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1. |
Record Nr. |
UNINA9910760293703321 |
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Autore |
Roy Shirshendu |
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Titolo |
Advanced Digital System Design : A Practical Guide to Verilog Based FPGA and ASIC Implementation / / by Shirshendu Roy |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (0 pages) |
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Disciplina |
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Soggetti |
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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 |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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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. |
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Sommario/riassunto |
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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 |
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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. |
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2. |
Record Nr. |
UNINA9910139240403321 |
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Autore |
Iosifescu Marius |
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Titolo |
Introduction to stochastic models / / Marius Iosifescu, Nikolaos Limnios, Gheorghe Oprisan ; series editor, Nikolaos Limnios |
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Pubbl/distr/stampa |
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London, : ISTE |
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Hoboken, N.J., : Wiley, 2010 |
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ISBN |
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9781118623527 |
1118623525 |
9781118623220 |
1118623223 |
9781299315655 |
1299315658 |
9780470394076 |
0470394072 |
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Edizione |
[1st edition] |
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Descrizione fisica |
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1 online resource (385 p.) |
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Collana |
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Applied stochastic methods series |
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Altri autori (Persone) |
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LimniosN (Nikolaos) |
OprisanGheorghe |
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Disciplina |
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Soggetti |
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Stochastic processes |
Stochastic models |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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"First published 2007 in France by Hermes Science/Lavoisier entitled: Modeles stochastiques"--t.p. verso. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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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 |
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Sommario/riassunto |
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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 |
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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 |
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