Contents

### **Preface XI**

and Jaime Meneses



Chapter 5 **Functional Verification of Digital Systems Using Meta-Heuristic Algorithms 73** Alfonso Martínez-Cruz, Ignacio Algredo-Badillo, Alejandro Medina-Santiago, Kelsey Ramírez-Gutiérrez, Prometeo Cortés-Antonio, Ricardo Barrón-Fernández, René Cumplido-Parra and Kwang-Ting Cheng


Chapter 7 **Neural Network Principles and Applications 115** Amer Zayegh and Nizar Al Bassam

#### Chapter 8 **Applications of General Regression Neural Networks in Dynamic Systems 133** Ahmad Jobran Al-Mahasneh, Sreenatha Anavatti, Matthew Garratt and Mahardhika Pratama

Preface

Digital system design requires unembellished simulation that eliminates potential risks and harm to users and manufacturers. Most of modern design and analysis tools are targeted at custom integrated circuits that are costly and time prohibitive to implement at high level designs. The purpose of this book is to provide a review on advanced digital system design and simulation through computer aided design (CAD) and machine learning tools. We present the practical applications of CAD and machine learning modeling and synthesis in digital system design to construct a basis for effective design and provide a tutorial of digi‐ tal systems functionality. We review theoretical principles, discrete mathematical models, computer simulations and machine learning methods in related areas. In this book, imple‐ mentation of frequency analysis methods is presented at software and hardware levels. Var‐ iable Digital Filter (VDF) is presented as one of the vastly used hardware processing tools in the field of digital systems. A detailed description is provided on the advanced design meth‐ ods of VDFs. Practical application of field-programmable gate array (FPGA) in a control sys‐ tem is presented in this book and an evolutionary algorithm is presented for functional verification of FPGA design. Deep learning has been used as an efficient tool for compres‐ sion of digital networks and increasing the processing speed. Some of the useful deep learn‐ ing methods have been introduced and the applications of them is presented in digital system design and verification. Several architectures are introduced and evaluated includ‐

ing general regression neural networks and convolutional neural networks.

researchers and users in this field.

As the editor of the book, I would like to acknowledge the contribution of the authors. These efforts allowed the updated materials in the field of digital systems to be available for the

**Dr. Vahid Asadpour**

Sadjad University of Technology

Research Scientist at University of California Los Angeles (UCLA)
