Neural, Parallel & Scientific Computations
Volume 2, 1994
CONTENTS
| R. J. Hathaway & J. C. Bezdek An iterative procedure for minimizing a generalized sum-of- squared-errors clustering criterion |
1 |
| L. P. Tay and D. J. Evans Fast learning artificial neural network (FLANN II) using the nearest neighbour recall |
17 |
| Doo-hyun Choi, Se-Young Oh, Hea-Dong Chang,
& Kwang-Ick Kim Nonlinear camera calibration using neural networks |
29 |
| Hugo Guterman Application of principal component analysis to the design of neural networks |
43
|
| D. H. Rao, M. M. Gupta, & P. N.
Nikiforuk Performance comparison of dynamic neural processor and recurrent networks |
55 |
| D. Zhang, L. Deng & M. I. Elmasry
Pipelined architecture for neural-network-based speech recognition |
81 |
| T. J. Stucke, G. G. Coghill, & G. A.
Creak The mind's eye: extracting structure from naturally variable objects |
93 |
| Eric B. Bartlett Self determination of input variable importance using neural networks |
103 |
| M. Hedge, M. Naraghi-Pour, & G.
Nandakumar On the capacity of constrained connectivity Hopfield neural networks |
115 |
| O. Abou-Rabia and Y.P. Boglaev Differential inequalities and convolution in parallel integration of ODEs |
131 |
| R. Neville and T. J. Stonham Adaptive associative reward-penalty algorithms for Sigma-Pi networks |
141 |
| Q. He and L. Kang Existence and stability of global solution for generalized Hopfield neural network system |
165 |
| P. D. Orkwis and J. H. George A comparison of CGS precondition methods for Newton's method solvers |
177 |
| S. Koksal, L. V. Fausett, and D. W. Fausett
Using vector Lyapunov functions for stability analysis of neural networks |
195 |
| P. P. Chu Neural networks as a parallel processing paradigm: potential and problems |
205 |
| V. Kreinovich Error estimates for indirect measurements is exponentially hard |
225 |
| R. Srikanth, C. Koutsougeras, and R. George
Hybrid charge clustering network: a heterogeneous neural network model |
235 |
| A. Jagota Contextual word recognition with a Hopfield-style net |
245 |
| Hsin-Chu Chen Increasing parallelism in the finite strip formulation: static analysis |
273 |
| M. Conti and C. Turchetti Approximation of dynamical systems by continuous-time recurrent approximate identity neural networks |
299 |
| F. S. King, P. Saratchandran, and N.
Sundararajan A study of parallel implementation of backpropagation neural networks on a transputer array |
321 |
| C. G. Jeong and H. Jeong A parallel algorithm for phonetic segmentation using mean field annealing |
333 |
| A. N. Jourjine Dynamic weight storage in pulse coded networks |
351 |
| G. Serpen and D. L. Livingston Analysis of the relationship between weight parameters and stability of solutions in Hopfield networks from dynamic systems viewpoint |
361 |
| C. N. Manikopoulos and R. Hormis Speech coding with neural-networks in adaptive DPCM |
373 |
| S. M. Bhandarkar and P. Jiang A comparison of task distribution patterns for matrix factorization on MIMD multiprocessor architectures |
385 |
| S. K. Aityan, R. A. Alo, and A. de Korvin
Introduction to the theory of weighted apertures |
407 |
| A. Olvera and C. Vargas Study of the continuation methods for periodic orbits of the Froeschle map |
421 |
| J. Kim, J. Ahn, C. S. Kim, H. Hwang, and S.
Cho Competitive learning neural network with dynamic output neuron generation |
431 |
| Z. Kewang, and P. Wang Numerical approximation of an unknown boundary term in a heat equation |
451 |
| P. C. Kainen, V. Kurkova, V. Kreinovich, and
O. Sirisaengtaksin Uniqueness of network parameterization and faster learning |
459 |
| M. Hegde, M. Naraghi-Pour, and G. Nandakumar Flexible learning rules for neural networks |
467 |
| L. Jin, P. N. Nikiforuk, and M. M. Gupta
The principles of dynamic neural units Part I: mechanism, dynamics, and stability |
491 |
| W. L. Miranker, and B. E. Willner A neural system for the animat |
517 |
| A. Dobnikar Genetic synthesis of task-oriented neural networks |
533 |
| Contents of volume 2
|
543 |
| Authors' Index
|
547 |