Understanding SONET / SDH and ATM (IEEE Press Understanding Science & Technology)
by Stamatios V. Kartalopoulos
"Optical communications and fiber technology are fast becoming key solutions for the increasing bandwidth demands of the 21st century. This introductory text provides practicing engineers, managers, and students with a useful guide to the latest developments and future trends of three major technologies: SONET, SDH, and ATM, and a brief introduction to legacy TDM communications systems. There are clear explanations of: * How ATM is mapped onto SONET/SDH * The role of IP networking with ATM...
This text provides basic concepts, algorithms and analysis of neural network models, with emphasis on the importance of knowledge in intelligent system design. It bridges the gap between artificial intelligence annd neural networks. The text provides a unified perspective, which could be used to integrate intelligence technologies.
Neurocomputing (A Bradford Book)
by James A. Anderson and Andras Pellionisz
In bringing together seminal articles on the foundations of research, the first volume of "Neurocomputing has become an established guide to the background of concepts employed in this burgeoning field. "Neurocomputing 2 collects thirty-nine articles covering network architecture, neurobiological computation, statistics and pattern classification, and problems and applications, that suggest important directions for the evolution of neurocomputing. Many of the most valuable practical ideas for ne...
Models of Neural Networks (Physics of Neural Networks, v. 2)
The theory of neural nets has two new paradigms: information coding through coherent firing of the neurons and structural feedback. As compared to traditional neural nets, spiking neurons provide an extra degree of freedom: time. This degree of freedom is realized by a coherent spiking of many neurons in the network, a nonlinear phenomenon. The other paradigm, feedback, is a dominant feature of the structural organization of the brain. This volume provides an in-depth analysis of both paradigms,...
Code Recognition and Set Selection with Neural Networks (Mathematical Modeling, v. 7)
by Clark Jeffries
Introduction to Neural Networks for Java, Second Edition
by Jeff Heaton
Leverage Python source code to revolutionize your short selling strategy and to consistently make profits in bull, bear, and sideways marketsKey FeaturesUnderstand techniques such as trend following, mean reversion, position sizing, and risk management in a short-selling contextImplement Python source code to explore and develop your own investment strategyTest your trading strategies to limit risk and increase profitsBook DescriptionIf you are in the long/short business, learning how to sell sh...
Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural networks using the Python ecosystemKey FeaturesGet to grips with building faster and more robust deep learning architecturesInvestigate and train convolutional neural network (CNN) models with GPU-accelerated libraries such as TensorFlow and PyTorchApply deep neural networks (DNNs) to computer vision problems, NLP, and GANsBook DescriptionIn order to build r...
Joint Source-Channel Coding of Discrete-Time Signals with Continuous Amplitudes (Communications and Signal Processing, #1)
by Norbert Goertz
This book provides the first comprehensive and easy-to-read discussion of joint source-channel encoding and decoding for source signals with continuous amplitudes. It is a state-of-the-art presentation of this exciting, thriving field of research, making pioneering contributions to the new concept of source-adaptive modulation.The book starts with the basic theory and the motivation for a joint realization of source and channel coding. Specialized chapters deal with practically relevant scenario...
Hands-On Machine Learning with Scikit-Learn, Keras, and Tensorflow
by Geron Aurelien
Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of the field are tackled, including artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods, including back-propagation; associative memory and Hopfield nets; and self-organization and feature maps. The traditionally difficult topic of adaptive resonance theory is clari...
Artificial intelligence is at the forefront of research and implementation in many industries including healthcare and agriculture. Whether it's detecting disease or generating algorithms, deep learning techniques are advancing exponentially. Researchers and professionals need a platform in which they can keep up with machine learning trends and their developments in the real world. The Handbook of Research on Applications and Implementations of Machine Learning Techniques provides innovative in...
Application of Neural Networks and Other Learning
Connectionist Models of Cognition and Perception II
by Howard Bowman and Christophe Labiouse
Proceedings of the Thirtieth International MATADOR Conference
The collected papers presented at the Thirtieth International Matador Conference, held at UMIST, Manchester on 31 March-1 April 1993. This year, in addition to the latest developments in traditional areas of machine tool technology, sessions on expert systems and neural networks have been included for the first time, reflecting the growing importance of artificial intelligence applications in manufacturing. Contains contributions from the following countries: Japan, USA, Hungary, Italy, Poland,...
Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size--small enough to run on a microcontroller. With this practical book you'll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices.Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who...