A new algorithm for learning in piecewise-linear neural networks

• Published in: Neural networks Vol. 13; no. 4; pp. 485 - 505
• Main Authors: Gad, E.F., Atiya, A.F., Shaheen, S., El-Dessouki, A.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.05.2000; Elsevier Science
• Subjects: Algorithms; Applied sciences; Computer Simulation; Convergence; Electric, optical and optoelectronic circuits; Electronics; Exact sciences and technology; Function approximation; Linear Models; Neural networks; Neural Networks (Computer); Function approximation; Neural networks; Convergence; Learning; Conjugate gradient method; Backpropagation algorithm; Classification; Error function; Neural network; Learning algorithm; Artificial intelligence; Hyperplane; Implementation; Optimization; Piecewise linearization

Piecewise-linear (PWL) neural networks are widely known for their amenability to digital implementation. This paper presents a new algorithm for learning in PWL networks consisting of a single hidden layer. The approach adopted is based upon constructing a continuous PWL error function and developin...