Here’s how deep learning neural networks are designed
In the world of machine learning, deep learning neural networks (DLNN) is the fastest growing field.
World Scientific's latest book "Deep Learning Neural Networks: Design and Case Studies" shows how DLNN can be a powerful computational tool for solving prediction, diagnosis, detection and decision problems based on a well-defined computational architecture.
The applications in this field serve as a major decision tool in Big Data applications. DLNN successfully applied to a broad field of applications ranging from computer security, speech recognition, image and video recognition to industrial fault detection, medical diagnostics and finance. Their range of applications covers almost any problem whose input data, performance evaluation and target decision can be numerically expressed.
The architecture of DLNN is based on principles of biological neural networks and have the ability to intelligently integrate any mathematical or logical algorithm into their decision process.
The book's contents include basic concepts of neural networks, back propagation, cognitron and neocognitron, deep learning convolutional neural networks, LAMSTAR-1 and LAMSTAR-2 neural networks, and case studies, amongst others.
This book retails at US$88 / £73 (hardcover) and US$48 / £40 (paperback). More information can be found at http://www.worldscientific.com/worldscibooks/10.1142/10190.
Authored by Daniel Graupe (University of Illinois, Chicago, USA), Deep Learning Neural Networks: Design and Case Studies is on sale in major bookstores, including Amazon, and retails for US$88/ £73 (hardcover) and US$48/ £40 (paperback). For more information on the book, please visit.
About World Scientific Publishing Co.
World Scientific Publishing is a leading independent publisher of books and journals for the scholarly, research, professional and educational communities. The company publishes about 600 books annually and about 130 journals in various fields. World Scientific collaborates with prestigious organizations like the Nobel Foundation, US National Academies Press, as well as its subsidiary, the Imperial College Press, amongst others, to bring high quality academic and professional content to researchers and academics worldwide. To find out more about World Scientific, please visit http://www.worldscientific.com. For more information, contact Jason Lim at [email protected]
About the author :
Daniel Graupe, Ph.D., is Emeritus Professor of Electrical and Computer Engineering, Emeritus Professor of Bioengineering and Emeritus Adjunct Professor of Neurology and Rehabilitation Medicine at the University of Illinois at Chicago where he co-directs the signal and image processing laboratory. Prior to joining the University of Illinois, he was the first Bodine Chair Professor of Electrical Engineering at Illinois Inst. of Technology, Chicago.
Dr. Graupe is Life Fellow of the IEEE (Institute of Electrical and Electronics Engineers). He received his BSME and BSEE degrees from the Technion, Israel Institute of Technology, and a Ph.D. in electrical engineering from the University of Liverpool, England.
Since becoming Emeritus Professor, he continued to direct his Lab on Control of Deep-Brain Stimulation at the University of Illinois, under a joint research program with the Department of Neurosurgery
He served as Associate Editor of the IEEE Transactions on Circuits and Systems, with responsibility to Signal Processing (1989-91) and of the IEEE Transactions on Neural Systems and Rehabilitation Engineering 2002-2004). He is presently associate editor of the International Journal of Software Engineering and Knowledge Engineering (with responsibility to neural networks), of Neurological Research (with responsibility to Neuroengineering), of Psychline and on the advisory board of the European Journal of Translational Myography (Basic & Appl. Myology) journal.
He is menber of the Executive Committee of the Board of Directors of the International Society of Bioelectromagnetism. He serves on several committees of the IEEE's Signal Processing Society and Bioengineering society.