WSEAS Transactions on
Print ISSN: 1790-5052
Volume 12, 2016
Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.
Volume 12, 2016
Title of the Paper: Efficient Multistep Nonlinear Time Series Prediction Involving Deterministic Chaos Based Local Reconstruction Methodologies and Multilayer Perceptron Neural Networks in Diode Resonator Circuits
Authors: D. A. Karras, M. P. Hanias
Abstract: A novel non-linear signal prediction method is presented using non linear signal analysis and deterministic chaos techniques in combination with an improved local reconstruction methodology and multilayer neural networks for a diode resonator chaotic circuit generated time series forecasting. Multisim is used to simulate the circuit and show the presence of chaos as well as to generate the time series data. The Time series analysis is performed by the method proposed by Grasberger and Procaccia, involving estimation of the correlation and minimum embedding dimension as well as of the corresponding Kolmogorov entropy. These parameters are used to construct the preprocessing step of a first stage of a one step / multistep predictor. This first stage involves, in the sequel a local reconstruction based approach. More specifically, it is suggested that by extracting a class of informative features coming from second order information, involving the topology of their neighbouring state vectors, from the state vectors of the local reconstruction approach then, significantly better results could be obtained with respect to chaotic time series reconstruction. In the second stage of the proposed method a multilayer neural network, trained with the conjugate gradient algorithm, is employed in order to provide the proper topology preserving error characteristics for the associated time series prediction. One of the novelties of the proposed two stage predictor lies on that the ANN involved could be employed as second order predictors, that is as error predictors of the non-linear signal analysis based forecasted values. This novel two stage chaotic signal forecasting technique is evaluated through an extensive experimental study.
Keywords: time series forecasting, non-linear signal analysis, diode, chaos, time series, correlation dimension, prediction, error prediction, neural networks, local reconstruction, Backpropagation error
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #27, pp. 218-226
Title of the Paper: Frequency Domain Identification of Autoregressive Models in the Presence of Additive Noise
Authors: Umberto Soverini, Torsten Söderström
Abstract: This paper describes a new approach for identifying autoregressive models from a finite number of measurements, in presence of additive and uncorrelated white noise. As a major novelty, the proposed approach deals with frequency domain data. In particular, two different frequency domain algorithms are proposed. The first algorithm is based on some theoretical results concerning the so–called dynamic Frisch Scheme. The second algorithm maps the AR identification problem into a quadratic eigenvalue problem. Both methods resemble in many aspects some other identification algorithms, originally developed in the time domain. The features of the proposed methods are compared each other and with those of other time domain algorithms by means of Monte Carlo simulations.
Keywords: System identification, Autoregressive models, Frisch Scheme, Discrete Fourier Transform
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #26, pp. 208-217
Title of the Paper: 3D Image Representation through Hierarchical Tensor Decomposition, Based on SVD with Elementary Tensor of size 2x2x2
Authors: Roumen Kountchev, Roumiana Kountcheva
Abstract: As it is known, groups of correlated 2D images of various kind could be represented as 3D images, which are mathematically described as 3rd order tensors. Various generalizations of the Singular Value Decomposition (SVD) exist, aimed at the tensor description reduction. In this work, new approach is presented for 3rd order tensor decomposition, where unlike the famous methods for decomposition components definition, iterative calculations are not used. The basic structure unit of the new decomposition is an elementary tensor (ET) of size 222, which builds the 3D tensors of size N×N×N, where N=2n. The decomposition of the single ЕТ is executed by using Hierarchical 2-level SVD, where (in each level) the SVD of size 2×2 (SVD2×2) is applied on all sub-matrices obtained after the elementary tensor unfolding. The so calculated new sub-matrices of the SVD2×2 in each hierarchical level, are rearranged in accordance with the lessening of their corresponding singular values. The computational complexity of the new tensor decomposition is lower than that of the decompositions, based on iterative methods, and permits parallel calculations for all SVD2×2 for the sub-matrices in a given hierarchical level.
Keywords: 3D images, tensor decomposition, Hierarchical SVD (HSVD), elementary tensor of size 2x2x2
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #25, pp. 199-207
Title of the Paper: Design of IIR Filters with Reduced Group Delay Ripple via Particle Swarm Optimization
Authors: Yasunori Sugita
Abstract: This paper presents a design method for infinite impulse response (IIR) filters with an approximately linear phase characteristic. The design problem of IIR digital filters is generally expressed as the minimization problem of the complex magnitude error which includes both the magnitude and phase information. However, the group delay response of the filter obtained by solving such design problem may be distant from the desired group delay. In this paper, the filter design problem is formulated as a magnitude error minimization problem having a maximum group delay error constraint and it is optimized using craziness based particle swarm optimization technique. As a result, the proposed method can design the IIR filters that satisfy the prespecified allowable errors of the group delay response. The usefulness of the proposed method is verified through some examples.
Keywords: IIR filter, Group delay error, Particle swarm optimization
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #24, pp. 203-209
Title of the Paper: Three-Dimensional Measurement Using Multiple Slits with a Random Dot Pattern - Multiple Slits and Camera Calibration -
Authors: Kumiko Yoshida, Kikuhito Kawasue
Abstract: Computer vision systems have been used to detect three-dimensional shape data of objects. Slit-laser sweeping or several pattern projections are generated during the recording process when using these systems. Generally, since the recording process requires time, it is necessary to temporarily stop the movement of both the measurement target and the measurement device during the recording process. In order to address this problem, we have developed a measurement system that projects multiple slits with random dots. Three-dimensional shape data can be detected by a single shot. In the proposed method, each slit must be identified in order to judge the projection direction. Random dots are projected onto the same area of multiple slits, and the pattern of random dots is used to identify the slit. In the present paper, an effective calibration method for the system and a method by which to separate each slit and dot pattern in the image are introduced.
Keywords: Calibration, Computer vision, Random dots, Point cloud, Multiple slits, Laser, Three-dimensional
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #23, pp. 192-202
Title of the Paper: Performance Study of the Smart Networks for Remote Sensing Image Textures Identification
Authors: Marrakchi Charfi Olfa, Mbainaibeye Jerome
Abstract: In this paper the performance evaluation of smart networks to identify highly heterogeneous textures remote sensing images was investigated. These networks are Feed Forward Neural Networks (FFNN), Quantum Neural Network (QNN) and Support Vector Machine (SVM). This evaluation is performed through an optimization training time and number of parameters of smart networks in the constraint to achieve optimal identification rate of the textures. The study also concerns the influence of the nature of heterogeneous textures on the choice of smart networks parameters to obtain elementary unit of textures. The objective is to study the impact of the textural information on the network design and considering that the samples of textures have a textural complexity due to the textural correlation and the overlapping rates of species in these textures. Textures bases used in this study are taken from different remote sensing images sources: an airborne radar image and an ASTER satellite whose resolutions are totally different. We have studied the influence of the spatial resolution on the textures identification and network performance relative to each of the two types of images.
Keywords: Smart networks, textures, classification, identification, remote sensing images
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #22, pp. 179-191
Title of the Paper: Combining Jaccard and Mahalanobis Cosine Distance to Enhance the Face Recognition Rate
Authors: Abdelghafour Abbad, Hamid Tairi
Abstract: Facial recognition has become the most dynamic biometric technology. In recent years, it has become a very powerful tool for recognition and authentication of biometric systems. To increase the performance of face recognition algorithms, we propose a new face recognition method which consists in combining, Jaccard and Mahalanobis Cosine distance (JMahCosine). Recognition Rates obtained on a facial recognition system shows the interest of the proposed technique, compared to others methods of literature. Our system has been tested on different databases accessible to the public, namely ORL, YALE and Sheffield.
Keywords: Facial biometrics, Dissimilarity Measure, Jaccard distance, Mahalanobis Cosine distance, recognition Rate
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #21, pp. 171-178
Title of the Paper: Sleeve Bearing Fault Diagnosis and Classification
Authors: Yassine Elyassami, Khalid Benjelloun, Mohamed El Aroussi
Abstract: Sleeve bearing is a bearing without any rotating element but with a sliding component, it is an expensive component in special machinery elements. Their faults can damage other principal machinery parts like shafts and cause very important production lost and high maintenance cost. Because those bearings are a special case just a few researchers studied detection and classification of sleeve bearing faults by data vibration analysis. In this paper we present a diagnosis and a classification methodologies applied to different kind of sleeve bearing damages. We develop a two-lobe bore sleeve bearing vibration database from a set of large induction machine equipment, then we use temporary and frequency process to diagnose faults, in the final step we classify those sleeve bearings by different methods based on entropy extraction and fault classifiers fusion.
Keywords: Condition monitoring, Machine vibration, Diagnosis, Fault classification, Sleeve bearing
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #20, pp. 163-170
Title of the Paper: Study and Application of the Transfer Characteristics of the Mount under the Testing Correlation
Authors: Zhang Yuanyuan, Xin Jianghui, Zhou Xiang, Zhou Yang
Abstract: The vibration from different moving structure in car traveling is interactional, judging interactional relations among structures reasonably is premise to analyze the mount system characteristics. In paper, the transfer characteristics law with the acceleration being exciting are analyzed and summarized, the mount transfer characteristic of the car in driving is derived, and combining with experiment, calculation flow of the mount isolation characteristic is designed, experiments with independent power system excitation test, independent road excitation test, driving test in steady speed are proposed to obtain interference components, common frequency components and the corresponding proportion between vibration source; and finally, by the actual driving testing and data processing, the time-domain isolation characteristics of the power system mounts are obtained. The proposed method can effectively improve the evaluation precision of the mount system and transfer characteristics it is a certain engineering application value.
Keywords: Vibration, Mount, Relevant, Isolation rate, Acceleration transfer characteristics
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #19, pp. 155-162
Title of the Paper: Niche Particle Swarm Optimization Combined with Chaotic Mutation Application in Image Enhancement
Authors: Yu Dong, Lin-Lin Zhao
Abstract: A niche chaotic mutation particle swarm optimization (NCPSO) algorithm is proposed to overcome the problem of loss details of images, the contrast is not obvious and poor adaptability in traditional image enhancement methods. In this algorithm, niching methods and elimination strategy are introduced to improve the global optimization ability. Mutative scale chaos mutation algorithm has refined local traversal search performance, which makes the algorithm has higher searching precision. The results indicate that image enhancement based on the algorithm has such advantage as image detail clearly, strong contrast and excellent versatility.
Keywords: Image enhancement, Niche particle swarm, Chaotic mutation, Particle swarm optimization
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #18, pp. 148-154
Title of the Paper: QRS Detection and PVC Beat Recognition Using a Generalised Teager Energy Operator
Authors: Anwar Al-Shrouf
Abstract: This paper presents a novel algorithm for automatic QRS complex detection and premature ventricular contraction (PVC) beat recognition based on a generalised Teager energy operator (GTEO). The algorithm is divided into two stages: QRS detection and PVC beat recognition. An optimal GTEO order is determined for each stage. A second order GTEO is used for QRS detection, and a seventh order GTEO is used for PVC beat recognition. The proposed algorithm was tested using ECG signals from two recognised arrhythmia databases, the MIT-BIH and the AHA database. The signals chosen contained PVC beats as well as normal beats. Sensitivity and specificity parameters were used to measure the accuracy of the proposed algorithm. The main advantages of using a GTEO are simplicity, robustness and speed. The sensitivities achieved using the proposed algorithm were 99.5% for QRS detection and 97.4% for PVC recognition. The specificities achieved were 99.8% for QRS detection and 99.1% for PVC beat recognition.
Keywords: Teager Energy, ECG, QRS Detection, PVC Recognition, SA Node, Purkinje Fibres
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #17, pp. 141-147
Title of the Paper: Path Following Algorithm and Experiments for an Incomplete Symmetry Unmanned Amphibious Platform
Authors: Yulong Hua, Wei Sun, Baoshan Chi, Guoqiang Liu
Abstract: The path following problem of incomplete symmetry unmanned amphibious platform was addressed. Considering the environmental disturbances the mathematical model of unmanned amphibious platform was established, and its control inputs were transformed from force and torque to water gate openings and pedal position. The path following error system, which was obtained after the former model being described in Serret-Frenet coordinate, was separated into two cascade subsystems, i.e., the position following subsystem and the orientation & surge velocity following subsystem. Then the equivalence between the second subsystem and the path following error system was proved on the basis of cascade theory. The globally asymptotically stable controller of orientation & surge velocity following subsystem was established based on backstepping adaptive sliding mode control method. The mathematic simulations and experimental tests were carried out, which illustrated that it was available for the incomplete symmetry unmanned amphibious platform to track the straight-line and circle path robustness under disturbances.
Keywords: incomplete symmetry, unmanned amphibious platform, path following, Serret-Frenet frame, cascade theory, backstepping adaptive sliding mode control
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #16, pp. 130-140
Title of the Paper: Quality Assessment on Digital Images Using Parallel Non-Linear De-Blocking Model
Authors: D. Ferlin Deva Shahila, S. H. Krishnaveni
Abstract: To achieve a non-linear de-blocking on digital images, a framework called Parallel Non-linear De-Blocking (PN-DB) is developed in this paper. The PN-DN framework is developed to reduce the blocking artifacts and therefore to increase the image quality. In PN-DB framework, Adaptive Structures Directional Lifting (ASDL) with Discrete Wavelet Transform (DWT) performs multi scale histogram representation on digital images. The ASDL changes the sampling matrix into sub-regions of digital images and improves the performance of the lossy-to-lossless image coding application. In the ASDL scheme, a Sinc interpolation filter with constant coefficient is adopted to interpolate both straight and perpendicular direction of the digital image aiming to minimize prediction errors during coding results. Finally, lossy and lossless digital image coding results of the PN-DB framework are shown to validate the advantage of the proposed structure. The performance of the proposed framework is evaluated using The Manuscripts and Archives Digital Images Database (MADID). Simulations conducted with MADID show the performance improvement in image quality by minimizing prediction error during coding results that further reduced the blocking artifacts in an extensive manner.
Keywords: Multimedia, Non-linear de-blocking, Artifacts, Adaptive Structures, Directional Lifting, Discrete Wavelet Transform, Sinc interpolation filter
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #15, pp. 118-129
Title of the Paper: Visibility Estimation of Road Signs Considering Detect-Ability Factors for Driver Assistance Systems
Authors: Jafar J. Abukhait
Abstract: This paper proposes an automated system to estimate the visibility of road signs from the driver’s perspective in daytime using in-vehicle camera images. A set of detect-ability parameters such as surrounding simplicity, occlusion, and tilting of road sign were computed to estimate the overall sign visibility. Detectability is defined as the ability of the driver to locate road sign object from a scene and thus; it measures sign posting with respect to cluttered or complex environment. The proposed system can be deployed in Driver Assistance Systems (DAS) to control information provided to drivers, since providing too much information could lead to driver distraction. Road signs are classified according to their visibility level and thus; Driver Assistance Systems can use these visibility levels to warn drivers about road signs with less visibility and high importance. The proposed system consists of four stages: 1) road sign detection and shape recognition; 2) segmentation of surrounding regions; 3) detect-ability parameters measurement; and 4) visibility level determination. This paper proposes a visibility estimation system of road signs in the United States and experimental results are used to show its effectiveness. Visibility levels from the proposed system have been compared subjectively with human expert’s decisions where a notable agreement between both decisions has been gained.
Keywords: Road Sign Detection, Color Segmentation, Edge Detector, Driver Assistance System, Driver Safety Support Systems, Detect-ability, Visibility Estimation
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #14, pp. 111-117
Title of the Paper: Modified Matched Signal Transform for Parameter Estimation of Spread Spectrum Stretch Signal
Authors: Xiaodong Zeng
Abstract: The spread spectrum stretch (S-cubed) is a kind of hybrid signal which has the advantages of the expansion and wide instantaneous bandwidth, proved to be the potential option for low probability of intercept (LPI) radar and stealth communications. In this paper, the S-cubed model that superimposes a short, cyclically repeated, discrete phase code on linear frequency modulation (LFM) is presented. In order to extract the signal features, we formulate modified matched signal transform (MMST) and then propose a novel approach to estimate the parameters of S-cubed in MMST domain. Furthermore, the numerical simulation and parameter estimation robustness are also studied. The simulation results show that when signal to noise ratio (SNR) is -7dB, the probability of correct decision (PCD) of the chirp rate has reached 90%.
Keywords: spread spectrum stretch (S-cubed), modified matched signal transform (MMST), parameter estimation
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #13, pp. 102-110
Title of the Paper: A New Method of Image Quality Assessment
Authors: Shuang Liang, Guanxiang Wang, Shuli Wang, Yu Wang
Abstract: In image processing, one of the important items is how to measure the quality of an image. This paper attempts to establish an assessment model corresponding to mean human perception, or mean opinion score (MOS). Human vision system has a feature of being more sensitive to the brightness change of an area than to that of discrete points, and being more sensitive to the change of moderate brightness than to the change of very bright one and very dark one. According to such a feature, by defining brightness discrimination and error density, using gradient as well, this paper proposes a new method of image quality assessment. The new method is tested on TID2008 data and the results are compared with those of existing methods.
Keywords: image quality assessment, brightness discrimination, error density, gradient
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #12, pp. 94-101
Title of the Paper: Extended Evaluation of XZ-Shape Histogram for Human-Object Interaction Activity Recognition based on Kinect-Like Depth Image
Authors: M. A. As’ari, U. U. Sheikh, A. H. Omar, N. A. Zakaria, N. H. Mahmood
Abstract: In this paper, we extend our previous work in investigating the performance of XZ-shape histogram for recognizing human performing activities of daily living (ADLs) which focuses on human-object interaction activities based on Kinect-like depth image. The feasibility of XZ-shape histogram as well as general 3D shape descriptors namely; 1) shape distribution, 2) shape histogram, 3) global spin image and 4) local spin image, in recognizing human-object interaction was tested using RGBD-HOI dataset. Moreover, the proposed evaluation framework was formulated to infer the descriptors’ performance. It was found that, the XZ-shape histogram outperformed other general 3D shape descriptors that compares the performance inferred by the area under receiver operating characteristic curve (AUC-ROC). The results of this study not only demonstrate the implementation of 3D shape descriptor in the dynamic of human activity recognition but also challenge the other general 3D shape descriptor in terms of providing low dimension descriptor that capable in improving the discrimination power of human-object interaction activity recognition.
Keywords: human-object interaction, activities of daily living (ADLs), RGBD image, shape distribution, spin image, shape histogram
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #11, pp. 83-93
Title of the Paper: Image Characteristic Based Rate Control Algorithm for HEVC
Authors: Mayan Fei, Zongju Peng, Weiguo Chen, Fen Chen
Abstract: Rate control plays an important role in high quality video coding. In this paper, a rate control algorithm based on video characteristics is proposed. Firstly, we put forward a novel bit allocation algorithm for intra frame by analyzing the relationship among the image characteristic, bit per pixel and quantization step. The image gradient is used as image characteristic. In frame layer, different bit allocation model are applied according to frame type and assign the rational bit to frame according the complexity of video content. In largest coding unit (LCU) layer, it also chooses different strategies of bit allocation according to the type of LCU. To be more specific, the bit of a LCU without previously coded collocated LCU is assigned on the basis of its image complexity. Otherwise, the bit of a LCU is assigned by using the gradient of residual belonging to collocated LCU. Experimental results show that the proposed algorithm is better than the state-of-the-art rate control algorithm in terms of the accuracy of rate control and the coding quality, the average of PSNR has been improved by 0.15dB. Maximal PSNR gaining can reach 0.67dB.
Keywords: high efficiency video coding, rate control, image characteristic, largest coding unit
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #10, pp. 74-82
Title of the Paper: Performance Evaluation for the Two-Stage Cooperative Spectrum Sensing Scheme in Cognitive Radio
Authors: Hong Du, Shuang Fu, Guojun Shi, Weimin Li, Li Tian, Yanjun Meng
Abstract: In order to obtain more precise spectrum sensing performance in cognitive radio networks, a two-stage spectrum sensing approach is investigated. More specifically, a coarse spectrum sensing based on energy detection is introduced in the first stage. When the sensing decision is idle channel by coarse sensing, a fine spectrum sensing based on first order cyclostationary feature detection is exploited in the second stage. Moreover, the problem formulation and discussion of two-stage spectrum sensing is presented. Optimization algorithm is to maximize the throughput under the probability of error sensing constraint. Numerical results show that the sensing performance is improved significantly as opposed to conventional one stage spectrum sensing.
Keywords: cognitive radio, two-stage spectrum sensing, performance evaluation, energy detection, first order cyclostationary feature detection
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #9, pp. 68-73
Title of the Paper: Research on Data-Driven Energy Efficiency Optimization for Copper Flash Smelting Process
Authors: Yuncheng Dong, Junfeng Yao, Fei Long, Kunhong Liu, Chenhan Lin
Abstract: The characteristics of the copper flash smelting process include: multiple variable, nonlinearity, strong coupling, long delay and large fluctuations. With the development of computer technology and industrial automation, the complex industrial process has produced a large number of production data, which contains rich information for the mining of their patterns. In order to improve energy efficiency of the copper flash smelting process, this paper presents a method for minimizing energy consumption with meeting three technical indexes (matte grade, matte temperature and ratio of Fe to SiO2) as a constraint. Our method is composed of two main parts: firstly, the least square support vector machine model (LS-SVM) is used to predict three technical indexes and we compare it with back propagation (BP) neural network; secondly, the comprehensive energy consumption model based on particle swarm optimization (PSO) is used to find the operational-pattern of lowest energy consumption. Experimental results on practical production data show that our energy efficiency optimization method can accurately predict three technical indexes and find the operational-pattern leading to the lowest energy consumption.
Keywords: Copper Flash Smelting, Energy Consumption, Energy Efficiency Optimization, Three Technical Indexes, Least Square Support Vector Machine (LS-SVM), Particle Swarm Optimization (PSO)
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #8, pp. 58-67
Title of the Paper: Quantized Compressive Sensing Measurement Based on Improved Subspace Pursuit Algorithm
Authors: Liu Tao
Abstract: Recent research results in compressive sensing have shown that sparse signals can be recovered from a small number of random measurements. Whether quantized compressive measurements can provide an efficient representation of sparse signals in information-theoretic needs discuss. In this paper, the distortion rate functions are used as a tool to research the quantizing compressive sensing measurements bring about average distortion rate. Both uniform quantization and non-uniform quantization were considered, for quantized measurements, the improved subspace pursuit was adapted to accommodate quantization error based on the concept of consistency, and experimental results show that the improved algorithm significantly reduces the reconstruction distortion when compared to standard compressive sensing techniques.
Keywords: Compressive Sensing, Rate Distortion Function, Subspace Pursuit
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #7, pp. 51-57
Title of the Paper: RFID Indoor Positioning Based on RBF Interpolation and QPSO
Authors: Guixiong Liu, Yuanmao Li
Abstract: Aiming to reduce the drawbacks of traditional VIRE approach, such as inaccurate boundary positioning and poor results of virtual tags using linear interpolation, we propose a new algorithm based on Radial Basis Functions (RBF) interpolation method and Quantum-behaved Particle Swarm Optimization (QPSO) in this paper. In order to simulate the actual loss of RSSI better, the proposed approach uses smooth global RBF interpolation. In addition, QPSO is introduced to estimate the coordinates of tracking tags by conducting the objective function under optimized concepts. Numerical simulated experiments show that the general accuracy of the new method is approximately 0.167 meters, enjoying 84.5% increase compared to VIRE algorithm. Therefore, this approach has a relative high positioning precision.
Keywords: RFID, Indoor Positioning Algorithm, RBF, QPSO
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #6, pp. 45-50
Title of the Paper: Parameter Estimation of Harmonics in Multiplicative and Additive Noise Using Svd-Based ESPRIT
Authors: Shiyong Yang
Abstract: The frequency estimation of the harmonics in multiplicative and additive noise is investigated in this paper. To improve the frequency resolution of estimation, this paper proposes a SVD-based ESPRIT algorithm to estimate the frequency of harmonics in multiplicative and additive noise. The proposed SVD-based ESPRIT algorithm not only has high-resolution, but also is easy to be implemented in practice because it does not need peak searching. Simulation results clearly show the effectiveness of the proposed algorithm.
Keywords: Frequency estimation, multiplicative noise, frequency resolution, ESPRIT
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #5, pp. 39-44
Title of the Paper: Locally Adaptive Topology Preservation for Diffeomorphic Registration in Medical Imaging
Authors: Wei Liu, Lei-Ting Chen, Yun-Jin Chen, Guo-Cheng Yang, Hong-Bin Cai
Abstract: Diffeomorphic registration has become an active research field presently in medical image registration because of its the differential transformation with invertibility between anatomic individuals. In this paper, we propose a novel method named Locally Adaptive Topology Preservation for Diffeomorphic Registration, which is able to obtain accurate approximation for the local tangent space on the Lie group manifold and yield more plausible diffeomorphisms for spatial transformations. In order to incarnate the local geometric structure of the Lie group, the local linear approximation is adaptively optimized by selecting appropriate neighborhoods for each sample point. Furthermore, we investigate the Lie group structure of the Symmetric Positive Definite (SPD) matrices and evaluate the effectiveness of the algorithm by utilizing several sets of brain images. Experimental results demonstrate that our algorithm has a higher degree of topology preservation on a dense high-dimensional deformation field and performs better in the noisy setting.
Keywords: Diffeomorphic registration, Lie group, Neighborhood selection, Symmetric positive definite matrices, Medical images
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #4, pp. 28-38
Title of the Paper: Direction-of-Arrival Estimation of a Single Distorted Wavefront with Time-Variant Amplitude
Authors: Habti Abeida
Abstract: Direction-of-arrival (DOA) estimation algorithms in array processing applications have been developed under time-invariant wavefronts. In most applications this assumption is not realistic due to the nonhomogeneous propagation medium which can distort the wavefront received by the array. This paper extends the author’s previous work on signal-to-noise ratio (SNR) estimation, in developing a novel approach for estimating the DOA of a single narrow-band amplitude-distorted wavefront received by an arbitrary antenna array. The distorted-amplitude wavefront is assumed to vary according to the first order autoregressive AR(1) model with unknown coefficients. An approximate maximum-likelihood-based (ML-based) approach to estimate the DOA parameter is developed in the high SNR scenario. Compared with the classical ML method that requires computationally prohibitive multi-dimensional search, the proposed approach obtains the DOA estimate by maximizing a new cost function with respect to a single DOA parameter derived using Markov property of the AR(1) process. Compact Cramer- Rao lower bound (CRB) expressions for DOA parameter are derived for different kinds of time-varying fading amplitudes. High and low SNR approximation expressions for the CRB are also derived, that enable the derivation of a number of CRB properties. Finally, simulation results show the performance of the proposed estimator and validate the theoretical analysis.
Keywords: Direction-of-arrival (DOA) estimation, maximum likelihood (ML), Cramer Rao bound, Time-varying complex-valued AR(1) model
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #3, pp. 16-27
Title of the Paper: The Overcome of a Priori Information Problem in Sampling-Reconstruction Procedures of Gaussian Process Realizations
Authors: Vladimir Kazakov, Sviatoslav Afrikanov, Daniel Rodríguez
Abstract: The case of the Sampling-Reconstruction Procedure of Gaussian process realizations is investigated when a priori information about some parameters of a given process is unknown. The general case with unknown expectation, variance and covariance function is considered. The unknown parameters are estimated on the base of the received set of samples. In result we have some adaptive algorithms. The method of the investigation is founded on the mathematical simulations. The results of the investigation demonstrate that the covariance function has the great influence on the main characteristics of the Sampling-Reconstruction Procedure. So the measurement of the covariance function is the most important operation in the adaptive algorithms.
Keywords: A Priori Information Problem, Gaussian Process, Sampling - Reconstruction Procedure
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #2, pp. 10-15
Title of the Paper: Moving Target Tracking and Recognition Fusion Algorithm Based on Multi-Source
Authors: Qian Zhao, Siwei Kou, Zhaohua, Zeng
Abstract: For tracking accuracy of moving target in wide-area video surveillance system is not high, a tracking and recognition algorithm based on multi-source moving target is proposed. The fusion algorithm preliminarily determines candidate moving target by frame difference algorithm, and then matches candidate target with primary template by SIFT algorithm and treats the matching result as initial position, and at last tracks the target by CBWH algorithm. Experimental results show that the proposed algorithm can track the moving target well in the multi-source cases and has good robustness.
Keywords: Frame Difference, CBWH, SIFT, Fusion Algorithm, Target Tracking, Target Recognition
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 12, 2016, Art. #1, pp. 1-9