Transputing in numerical and neural network applications
Author(s)
Bibliographic Information
Transputing in numerical and neural network applications
(Transputer and occam engineering series, v. 30)
IOS Press, 1992
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Description and Table of Contents
Description
An examination of the use of transputers in numerical computing and neural networks. Topics covered include linear systems of equations and programming, fluid and molecular dynamics simulation, transformations, Kalman filtering and general numerical problems. Neural networks are discussed in ters of algorithms and simulation.
Table of Contents
- The parallel solution of systems of linear equations using iterative methods on transputer networks, Rudnei Dias da Cunha and Tim Hopkins
- parallel solution of linear programming using an adapted simplex method, Jian Luo and Gerard L. Reijns
- Cholesky factorization of sparse symmetric positive definite matrices on distributed parallel computers, Ron Levkovitz and Gautam Mitra
- parallel implementation of two algorithms to solve linear programming problems, Jian Luo and Gerard L. Reijns
- the branch-and-bound paradigm implemented on a network of transputers, G.P. McKeiwn et al
- parabolic problem solving on a transputer network, D.J. Evans and S. Chikohora
- the parallel solution of partial differential equations on transputer networks, Rudnei Dias da Cunha and Tim Hopkins
- multiprocessor algorithms for the solution of Fredholm integral equations, John A. Belward
- parallel processing for optimal control problems, Gurvinder Singh Virk
- two-dimensional FFT algorithms on parallel machines, G. Angelopoulos et al
- parallel Radix-2 FFT on transputers, A.U. Khan and N.M. Stephens
- a block-pipelined FFT transputing, Anatol G. Filin and Ivan E. Yukov
- application of transputer for adaptive filtering, John J. Soraghan et al
- parallel algorithm for recursive linear filtering on transputers, Yoshinori Takeuchi et al
- massive parallel genetic packing, Berthold Kroger et al
- on the solution of general linear systems and general matrix inversion using neural network architectures, K.G. Margaritis et al
- a general strategy for mapping neural networl models on transputer-based machines, Magali E. Azema-Barac
- a parallel approach to the simulation of complex movements, Paolo Franchi et al.
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