Designed as an introductory level textbook on Artificial Neural Networks at the postgraduate
and senior undergraduate levels in any branch of engineering, this self-contained and well …

With solid theoretical foundations and numerous potential applications, Blind Signal
Processing (BSP) is one of the hottest emerging areas in Signal Processing. This volume …

A class of nonlinear PCA (principal component analysis) type learning algorithms is derived
by minimizing a general statistical signal representation error. Another related algorithm is …

Soil moisture is a key variable that defines the land surface-atmosphere (boundary layer)
interactions, by contributing directly to the surface energy balance and water balance. This …

Programmiersprachen und-systeme zur Simulation neuronaler Netze eingegangen. Der
Schwerpunkt des Buches liegt damit im Zusammenfassen und Ordnen einer Breite von …

Correlative Learning: A Basis for Brain and Adaptive Systems provides a bridge between
three disciplines: computational neuroscience, neural networks, and signal processing. First …

A neural network learning paradigm based on information theory is proposed as a way to
perform, in an unsupervised fashion, redundancy reduction among the elements of the …

This study introduces the utility of the second-order neural network (SONN) method to model
the reference evapotranspiration (ET 0) in different climatic zones of India. The daily climate …

This monograph provides detailed background on the image processing problems
encountered in the food industry when automatic control and inspection systems are being …

In this chapter, the authors provide fundamental principles of Higher Order Neural Units
(HONUs) and Higher Order Neural Networks (HONNs) for modeling and simulation. An …