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Approximation theory and feedforward networks
Approximation of real functions by feedforward networks of the usual kind is shown to be based on the fundamental principle of approximation by piecewise-constant functions. Expand
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A Programming Language.
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Stability of fixed points and periodic orbits and bifurcations in analog neural networks
  • E. Blum, X. Wang
  • Mathematics, Computer Science
  • Neural Networks
  • 15 July 1992
We consider some neural networks which have interesting oscillatory dynamics and analyze stability and bifurcation properties. Expand
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Discrete-time neural networks as dynamical systems
This dissertation, viewing neural networks as dynamical systems, intends to give a coherent treatment on various dynamics of neural networks covering periodicity, bifurcation, chaos, and coupledExpand
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A theory of analytic functions in Banach algebras
Introduction. The present paper is concerned with the general problem of extending the classical theory of analytic functions of a complex variable. This question received the attention of HilbertExpand
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Towards a theory of semantics and compilers for programming languages
  • E. Blum
  • Computer Science
  • STOC '69
  • 5 May 1969
The concept of imbedding a programming language L into a formal system is introduced and used as the basis of defining the semantics &Fgr; of the language. Expand
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Algebraic Specification of Modules and Their Basic Interconnections
An algebraic specification concept for modules in software engineering is introduced which includes, in addition to a parameter and body part, explicit import and export interfaces. Expand
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A multi-processing implementation-oriented formal definition of Ada in SEMANOL
A formal definition of the syntax and semantics of Preliminary Ada has been designed and partially implemented as a metaprogram in the SEMANOL system. Expand
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Algebraic Theory of Module Specification with Constraints
The concept for modules in software engineering based on equational algebraic specifications is extended by a suitable notion of constraints. Expand
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