The analytical solution of gamma filter model

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn 2, Issue , 1997, Pages 685-689

  Chiang, Tai Wu ^a  

^a The University of Texas at Austin   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYTICAL APPROACH; GEOMETRICAL INTERPRETATION; LAGUERRE POLYNOMIAL; LINEAR VECTOR SPACE; OPTIMAL VALUES; OPTIMIZATION PROBLEMS; TEMPORAL RESOLUTION; TRAINING ALGORITHMS;

LINEAR TRANSFORMATIONS; MATHEMATICAL TRANSFORMATIONS; NEURAL NETWORKS; OPTIMIZATION; APPROXIMATION THEORY; LEARNING ALGORITHMS; MATHEMATICAL MODELS; POLYNOMIALS; SIGNAL FILTERING AND PREDICTION; VECTORS;

POLYNOMIALS; NEURAL NETWORKS;

CLASSICAL LAGUERRE POLYNOMIALS; GAMMA FILTER MODELS;

EID: 0030702552     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNN.1997.616104     Document Type: Conference Paper

References (5)

1. Bert De Vries and Jose C. Principe. The Gamma Model-A New Neural Model for Temporal Processing. Neural Networks, Vol. 5, pp. 565-576,1992.
2. Jose C. Principe, Jyh-Ming Kuo, and Samel Celebi. An Analysis of the Gamma Memory in Dynamic Neural Networks. IEEE Transactions on Neural Networks, Vol. 5 No. 2 March 1994
3. Steve Lawrence, Ah Chung Tsoi, Andrew D. Back, The Gamma MLP for Speech Phoneme Recognition. Advances in Neural Information Processing Systems 8, edited by D. Touretzky, M. Mozer and M. Hasselmo, MIT Press, 1996.
4. Szego, G. (1939). Orthogonal Polynomials. Providence, RI: American Mathematical Society.
5. Michael Reed, Barry Simon. Method of Modern Mathematical Physics I: Functional Analysis.