Abstract: We present a description of a set of 26 algorithms on neural networks and indicate the area where the algorithms could be applied. All algorithms are a part of the monograph (2009) Neural Networks. Mathematical Foundation, Algorithms and Applications, authors Nicolae Popoviciu and Floarea Baicu. Each algorithm has its mathematical foundation and the algorithms treat many aspects related with neural networks. We enumerate several directions: separable sets, supervised learning, BKP, MLP geometric algorithm, SOM competitive learning, ISODATA , Kohonen competitive algorithm, ART1 competitive algorithm, stock-recall problem, sales traveling problem, c-means algorithm for prototype vectors, RBF algorithms in batch version and sequential version, Householder decomposition etc. All algorithms are described step by step and are illustrated by many numerical examples.

Brief Biography of the Speaker:
Popoviciu Nicolae is PhD in mathematics (from 1976), professor at Hyperion University of Bucharest, Romania, Faculty of Mathematics-Informatics and the dean of this faculty. His area of competence contains: stochastic processes and Markov decision problems, integral transforms (continuous, discrete) and field theory, mathematical programming and optimization models, artificial neural networks and applications. He is the first author of 18 books (all in Romanian language) and the first author of 89 papers (almost all in English language). His recently book Neural Networks. Mathematical Foundation, Algorithms and Applications (2009) is a monograph on the algorithms of neural networks with application. Professor Popoviciu is member of Romanian Society of Mathematics and member of the Romanian Probability and Statistics Society. He has participated to many WSEAS International Conference as plenary speaker or author (Romania, Greece, Turkey, Bulgaria etc.).