Book Statistics
1 Views
0 Comments
0 Rating

Neural Networks and Computing

Description

This book covers neural networks with special emphasis on advanced learning methodologies and applications. It includes practical issues of weight initializations, stalling of learning, and escape from a local minima, which have not been covered by many existing books in this area. Additionally, the book highlights the important feature selection problem, which baffles many neural networks practitioners because of the difficulties handling large datasets. It also contains several interesting IT, engineering and bioinformatics applications.

Keywords

radial�basis�function �weight�elimination�method �regularized�objective�function �weight�decay�method �penalized�optimization �clustering�validity�index �confidence�upper�bound child�neurons �nearest�neuron �last�hidden�layer �load�consumption �feature�selection�scheme �cumulant�term �noise�perturbation �wavelet�network �gradient�descent�optimization perceptron�model �nearest�regions �bias�node �momentum�coefficient �classification�dataset �winner�neuron

Download & Read Options

Neural Networks and Computing.pdf

PDF

Reader's Comments (0)

Login to Comment
No Comments Yet

Be the first to share your thoughts about this book!