High Dimensional Neurocomputing
Growth, Appraisal and Applications
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Beschreibung
The book presents a coherent understanding of computational intelligence from the perspective of what is known as "intelligent computing" with high-dimensional parameters. It critically discusses the central issue of high-dimensional neurocomputing, such as quantitative representation of signals, extending the dimensionality of neuron, supervised and unsupervised learning and design of higher order neurons. The strong point of the book is its clarity and ability of the underlying theory to unify our understanding of high-dimensional computing where conventional methods fail. The plenty of application oriented problems are presented for evaluating, monitoring and maintaining the stability of adaptive learning machine. Author has taken care to cover the breadth and depth of the subject, both in the qualitative as well as quantitative way. The book is intended to enlighten the scientific community, ranging from advanced undergraduates to engineers, scientists and seasoned researchers in computational intelligence.
The book presents a coherent understanding of computational intelligence from the perspective of what is known as "intelligent computing" with high-dimensional parameters. It critically discusses the central issue of high-dimensional neurocomputing, such as quantitative representation of signals, extending the dimensionality of neuron, supervised and unsupervised learning and design of higher order neurons. The strong point of the book is its clarity and ability of the underlying theory to unify our understanding of high-dimensional computing where conventional methods fail. The plenty of application oriented problems are presented for evaluating, monitoring and maintaining the stability of adaptive learning machine. Author has taken care to cover the breadth and depth of the subject, both in the qualitative as well as quantitative way. The book is intended to enlighten the scientific community, ranging from advanced undergraduates to engineers, scientists and seasoned researchers in computational intelligence.
A novel approach for second generation of neurocomputing Provides analytical approach towards computational intelligence Discusses applications over wide spectrum of problems in single and high dimensions Helps to develop concepts and aptitude towards high-dimensional neurocomputing Includes solution for single-dimensional problems through two-dimensional neural networks Presents multivariate statistical techniques in complex domain focused on biometric applications Includes supplementary material: sn.pub/extras
Autor*in
Bipin Kumar Tripathi
Themen in »High Dimensional Neurocomputing«
Activation Functions on Plane High Dimensional Learning Algorithms High Dimensional Neural Network High Order Neurons Models Multivariate Statistical Analysis