"Digital Systems" ed. by Vahid Asadpour

This book provides an approach toward the applications and principle theory of digital signal processing in modern intelligent systems, biological engineering, telecommunication, and information technology. Assuming the reader already has prior knowledge of signal processing theory, this book will be useful for finding novel methods that fit special needs in digital signal processing (DSP). This book is a practical reference that places the emphasis on principles and applications of DSP in digital systems. It covers a broad area of digital systems and applications of machine learning methods including convolutional neural networks, evolutionary algorithms, adaptive filters, spectral estimation, data compression and functional verification.

The combination of signal processing and intelligent systems in hybrid structures rather than serial or parallel processing provide the best mechanism that is a better fit with the comprehensive nature of human.

The level of the book is ideal for professional DSP users and useful for graduate students who are looking for solutions to their design problems. The theoretical principles provide the required base for comprehension of the methods and application of modifications for the special needs of practical projects.


Contents
1 Fourier Transform Profilometry in LabVIEW
2 Recent Advances in Variable Digital Filters
3 Electrostatic Discharge Protection and Latch-Up Design and Methodologies for ASIC Development
4 Design of Controller for Brushless Direct Current Motors Using FPGA
5 Functional Verification of Digital Systems Using Meta-Heuristic Algorithms
6 Efficient Deep Learning in Network Compression and Acceleration
7 Neural Network Principles and Applications
8 Applications of General Regression Neural Networks in Dynamic Systems