1.

Record Nr.

UNINA9910760293703321

Autore

Roy Shirshendu

Titolo

Advanced Digital System Design : A Practical Guide to Verilog Based FPGA and ASIC Implementation / / by Shirshendu Roy

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2024

ISBN

3-031-41085-8

Edizione

[1st ed. 2024.]

Descrizione fisica

1 online resource (0 pages)

Disciplina

621.381

Soggetti

Electronic circuits

Computers

Computer-aided engineering

Electrical engineering

Electronic Circuits and Systems

Computer Hardware

Computer-Aided Engineering (CAD, CAE) and Design

Electrical and Electronic Engineering

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Binary Number System -- Basics of Verilog HDL -- Basic Combinational Circuits -- Basic Sequential Circuits -- Memory Design -- Finite State Machines -- Design of Adder Circuits -- Design of Multiplier Circuits -- Division and Modulous Operation -- Square Root and its Reciprocal -- CORDIC Algorithm -- Floating Point Architectures -- Timing Analysis -- Digital System Implementation -- Low Power Digital System Design -- Digital System Design Examples.

Sommario/riassunto

The book is designed to serve as a textbook for courses offered to undergraduate and graduate students enrolled in electrical, electronics, and communication engineering. The objective of this book is to help the readers to understand the concepts of digital system design as well as to motivate the students to pursue research in this field. Verilog Hardware Description Language (HDL) is preferred in this book to realize digital architectures. Concepts of Verilog HDL are discussed in a separate chapter and many Verilog codes are given in this book for



better understanding. Concepts of system Verilog to realize digital hardware are also discussed in a separate chapter. The book covers basic topics of digital logic design like binary number systems, combinational circuit design, sequential circuit design, and finite state machine (FSM) design. The book also covers some advanced topics on digital arithmetic like design of high-speed adders, multipliers, dividers, square root circuits, and CORDIC block. The readers can learn about FPGA and ASIC implementation steps and issues that arise at the time of implementation. One chapter of the book is dedicated to study the low-power design techniques and another to discuss the concepts of static time analysis (STA) of a digital system. Design and implementation of many digital systems are discussed in detail in a separate chapter. In the last chapter, basics of some advanced FPGA design techniques like partial re-configuration and system on chip (SoC) implementation are discussed. These designs can help the readers to design their architecture. This book can be very helpful to both undergraduate and postgraduate students and researchers.

2.

Record Nr.

UNINA9910139240403321

Autore

Iosifescu Marius

Titolo

Introduction to stochastic models / / Marius Iosifescu, Nikolaos Limnios, Gheorghe Oprisan ; series editor, Nikolaos Limnios

Pubbl/distr/stampa

London, : ISTE

Hoboken, N.J., : Wiley, 2010

ISBN

9781118623527

1118623525

9781118623220

1118623223

9781299315655

1299315658

9780470394076

0470394072

Edizione

[1st edition]

Descrizione fisica

1 online resource (385 p.)

Collana

Applied stochastic methods series

Altri autori (Persone)

LimniosN (Nikolaos)

OprisanGheorghe

Disciplina

519.2/3

Soggetti

Stochastic processes

Stochastic models



Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

"First published 2007 in France by Hermes Science/Lavoisier entitled: Modeles stochastiques"--t.p. verso.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Cover; Introduction to Stochastic Models; Title Page; Copyright Page; Table of Contents; Preface; Chapter 1. Introduction to Stochastic Processes; 1.1. Sequences of random variables; 1.2. The notion of stochastic process; 1.3. Martingales; 1.3.1. Stopping time; 1.3.2. Discrete-time martingales; 1.3.3. Martingale convergence; 1.3.4. Square integrable martingales; 1.4. Markov chains; 1.4.1. Markov property; 1.4.2. Transition function; 1.4.3. Strong Markov property; 1.5. State classification; 1.5.1. Stationary probability; 1.6. Continuous-time Markov processes; 1.6.1. Transition function

1.6.2. Kolmogorov equations1.7. Semi-Markov processes; 1.7.1. Markov renewal processes; 1.7.2. Semi-Markov processes; Chapter 2. Simple Stochastic Models; 2.1. Urn models; 2.2. Random walks; 2.3. Brownian motion; 2.3.1. Introduction; 2.3.2. Basic properties; 2.4. Poisson processes; 2.5. Birth and death processes; Chapter 3. Elements of Markov Modeling; 3.1. Markov models: ideas, history, applications; 3.2. The discrete-time Ehrenfest model; 3.2.1. The microscopic chain; 3.2.2. The macroscopic chain; 3.2.3. Some characteristics of the Ehrenfest model

3.2.4. The discrete-time Ehrenfest model: history, generalizations, similar models3.3. Markov models in genetics; 3.3.1. Laws of heredity and mathematics; 3.3.2. Haploid models; 3.3.3. Models with two genotypes and without mutations; 3.3.4. Models with several genotypes and without mutations; 3.3.5. Models with two genotypes and mutations; 3.3.6. Models with several genotypes and mutations; 3.3.7. Models with partitioned population; 3.3.8. Genealogy models for large size populations; 3.4. Markov storage models; 3.4.1. Discrete-time models; 3.4.2. Continuous-time models

3.4.3. A generalized storage model3.5. Reliability of Markov models; 3.5.1. Introduction to reliability; 3.5.2. Some classes of survival distributions; 3.5.3. Discrete-time models; 3.5.4. Continuous-time models; Chapter 4. Renewal Models; 4.1. Fundamental concepts and examples; 4.2. Waiting times; 4.3. Modified renewal processes; 4.4. Replacement models; 4.5. Renewal reward processes; 4.6. The risk problem of an insurance company; 4.7. Counter models; 4.7.1. Type I counters; 4.7.2. Type II counters; 4.8. Alternating renewal processes; 4.9. Superposition of renewal processes

4.10. Regenerative processesChapter 5. Semi-Markov Models; 5.1. Introduction; 5.2. Markov renewal processes; 5.2.1. Definitions; 5.2.2. Markov renewal theory; 5.3. First-passage times and state classification; 5.3.1. Stationary distribution and asymptotic results; 5.4. Reliability; 5.5. Reservoir models; 5.5.1. Model I; 5.5.2. Model II; 5.6. Queues; 5.6.1. The G/M/1 queue; 5.6.2. The M/G/1 queue; 5.7. Digital communication channels; Chapter 6. Branching Models; 6.1. The Bienaymé-Galton-Watson model; 6.1.1. Historical considerations; 6.1.2. Some elementary results; 6.1.3. A fundamental example

6.1.4. Extinction probability: critical theorem

Sommario/riassunto

This book provides a pedagogical examination of the way in which stochastic models are encountered in applied sciences and techniques such as physics, engineering, biology and genetics, economics and social sciences. It covers Markov and semi-Markov models, as well as



their particular cases: Poisson, renewal processes, branching processes, Ehrenfest models, genetic models, optimal stopping, reliability, reservoir theory, storage models, and queuing systems. Given this comprehensive treatment of the subject, students and researchers in applied sciences, as well as anyone looking for an introduc