The authors examine topics in modern physics and offer a unitary and original treatment of the fundamental problems of the dynamics of physical systems, as well as a description of the nuclear matter within a framework of general relativity. They show that some physical phenomena studied at two different resolution scales (e.g....

In numerous problems, the student is asked to...

This is the first book to focus on the problem of ensuring the correctness of floating-point hardware designs through mathematical methods.  Formal Verification of Floating-Point Hardware Design advances a verification methodology based on a unified theory of register-transfer logic and floating-point arithmetic that has...

This book applies generalized fractional differentiation techniques of Caputo, Canavati and Conformable types to a great variety of integral inequalities e.g. of Ostrowski and Opial types, etc. Some of these are extended to Banach space valued functions. These inequalities have also great impact in numerical analysis, stochastics and...

Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively from easy to more complex, orienting its content about knowledge transfer from the viewpoint of machine intelligence. It adopts the methodology from graphical theory, mathematical...

Discover more insight about deep learning algorithms with Swift for TensorFlow. The Swift language was designed by Apple for optimized performance and development whereas TensorFlow library was designed by Google for advanced machine learning research. Swift for TensorFlow is a combination of both...