Wing-Shan Tam – författare

A practical overview of CMOS circuit design, this book covers the technology, analysis, and design techniques of voltage reference circuits.  The design requirements covered follow modern CMOS processes, with an emphasis on low power, low voltage, and low temperature coefficient voltage reference design. Dedicating a chapter to each stage of the design process, the authors have organized the content to give readers the tools they need to implement the technologies themselves. Readers will gain an understanding of device characteristics, the practical considerations behind circuit topology, and potential problems with each type of circuit.  Many design examples are used throughout, most of which have been tested with silicon implementation or employed in real-world products. This ensures that the material presented relevant to both students studying the topic as well as readers requiring a practical viewpoint.   Covers CMOS voltage reference circuit design, from the basics through to advanced topicsProvides an overview of basic device physics and different building blocks of voltage reference designsFeatures real-world examples based on actual silicon implementationIncludes analytical exercises, simulation exercises, and silicon layout exercises, giving readers guidance and design layout experience for voltage reference circuitsSolution manual available to instructors from the book’s companion websiteThis book is highly useful for graduate students in VLSI design, as well as practicing analog engineers and IC design professionals. Advanced undergraduates preparing for further study in VLSI will also find this book a helpful companion text.

A practical overview of CMOS circuit design, this book covers the technology, analysis, and design techniques of voltage reference circuits.  The design requirements covered follow modern CMOS processes, with an emphasis on low power, low voltage, and low temperature coefficient voltage reference design. Dedicating a chapter to each stage of the design process, the authors have organized the content to give readers the tools they need to implement the technologies themselves. Readers will gain an understanding of device characteristics, the practical considerations behind circuit topology, and potential problems with each type of circuit.  

Many design examples are used throughout, most of which have been tested with silicon implementation or employed in real-world products. This ensures that the material presented relevant to both students studying the topic as well as readers requiring a practical viewpoint.  

Covers CMOS voltage reference circuit design, from the basics through to advanced topics Provides an overview of basic device physics and different building blocks of voltage reference designs Features real-world examples based on actual silicon implementation Includes analytical exercises, simulation exercises, and silicon layout exercises, giving readers guidance and design layout experience for voltage reference circuits Solution manual available to instructors from the book’s companion website

This book is highly useful for graduate students in VLSI design, as well as practicing analog engineers and IC design professionals. Advanced undergraduates preparing for further study in VLSI will also find this book a helpful companion text.

A practical overview of CMOS circuit design, this book covers the technology, analysis, and design techniques of voltage reference circuits.  The design requirements covered follow modern CMOS processes, with an emphasis on low power, low voltage, and low temperature coefficient voltage reference design. Dedicating a chapter to each stage of the design process, the authors have organized the content to give readers the tools they need to implement the technologies themselves. Readers will gain an understanding of device characteristics, the practical considerations behind circuit topology, and potential problems with each type of circuit.  

Many design examples are used throughout, most of which have been tested with silicon implementation or employed in real-world products. This ensures that the material presented relevant to both students studying the topic as well as readers requiring a practical viewpoint.  

Covers CMOS voltage reference circuit design, from the basics through to advanced topics Provides an overview of basic device physics and different building blocks of voltage reference designs Features real-world examples based on actual silicon implementation Includes analytical exercises, simulation exercises, and silicon layout exercises, giving readers guidance and design layout experience for voltage reference circuits Solution manual available to instructors from the book’s companion website

This book is highly useful for graduate students in VLSI design, as well as practicing analog engineers and IC design professionals. Advanced undergraduates preparing for further study in VLSI will also find this book a helpful companion text.

This book provides a comprehensive study in digital image interpolation with theoretical, analytical and Matlab® implementation. It includes all historically and practically important interpolation algorithms, accompanied with Matlab® source code on a website, which will assist readers to learn and understand the implementation details of each presented interpolation algorithm. Furthermore, sections in fundamental signal processing theories and image quality models are also included. The authors intend for the book to help readers develop a thorough consideration of the design of image interpolation algorithms and applications for their future research in the field of digital image processing. Introduces a wide range of traditional and advanced image interpolation methods concisely and provides thorough treatment of theoretical foundationsDiscusses in detail the assumptions and limitations of presented algorithmsInvestigates a variety of interpolation and implementation methods including transform domain, edge-directed, wavelet and scale-space, and fractal based methodsFeatures simulation results for comparative analysis, summaries and computational and analytical exercises at the end of each chapterDigital Image Interpolation in Matlab® is an excellent guide for researchers and engineers working in digital imaging and digital video technologies. Graduate students studying digital image processing will also benefit from this practical reference text.

This book provides a comprehensive study in digital image interpolation with theoretical, analytical and Matlab® implementation. It includes all historically and practically important interpolation algorithms, accompanied with Matlab® source code on a website, which will assist readers to learn and understand the implementation details of each presented interpolation algorithm. Furthermore, sections in fundamental signal processing theories and image quality models are also included. The authors intend for the book to help readers develop a thorough consideration of the design of image interpolation algorithms and applications for their future research in the field of digital image processing.

Introduces a wide range of traditional and advanced image interpolation methods concisely and provides thorough treatment of theoretical foundations Discusses in detail the assumptions and limitations of presented algorithms Investigates a variety of interpolation and implementation methods including transform domain, edge-directed, wavelet and scale-space, and fractal based methods Features simulation results for comparative analysis, summaries and computational and analytical exercises at the end of each chapter

Digital Image Interpolation in Matlab® is an excellent guide for researchers and engineers working in digital imaging and digital video technologies. Graduate students studying digital image processing will also benefit from this practical reference text. 

This book provides a comprehensive study in digital image interpolation with theoretical, analytical and Matlab® implementation. It includes all historically and practically important interpolation algorithms, accompanied with Matlab® source code on a website, which will assist readers to learn and understand the implementation details of each presented interpolation algorithm. Furthermore, sections in fundamental signal processing theories and image quality models are also included. The authors intend for the book to help readers develop a thorough consideration of the design of image interpolation algorithms and applications for their future research in the field of digital image processing.

Introduces a wide range of traditional and advanced image interpolation methods concisely and provides thorough treatment of theoretical foundations Discusses in detail the assumptions and limitations of presented algorithms Investigates a variety of interpolation and implementation methods including transform domain, edge-directed, wavelet and scale-space, and fractal based methods Features simulation results for comparative analysis, summaries and computational and analytical exercises at the end of each chapter

Digital Image Interpolation in Matlab® is an excellent guide for researchers and engineers working in digital imaging and digital video technologies. Graduate students studying digital image processing will also benefit from this practical reference text. 

Presents a review of image denoising algorithms with practical MATLAB implementation guidance Digital Image Denoising in MATLAB provides a comprehensive treatment of digital image denoising, containing a variety of techniques with applications in high-quality photo enhancement as well as multi-dimensional signal processing problems such as array signal processing, radar signal estimation and detection, and more. Offering systematic guidance on image denoising in theories and in practice through MATLAB, this hands-on guide includes practical examples, chapter summaries, analytical and programming problems, computer simulations, and source codes for all algorithms discussed in the book. The book explains denoising algorithms including linear and nonlinear filtering, Wiener filtering, spatially adaptive and multi-channel processing, transform and wavelet domains processing, singular value decomposition, and various low variance optimization and low rank processing techniques. Throughout the text, the authors address the theory, analysis, and implementation of the denoising algorithms to help readers solve their image processing problems and develop their own solutions. Explains how the quality of an image can be quantified in MATLAB Discusses what constitutes a “naturally looking” image in subjective and analytical terms Presents denoising techniques for a wide range of digital image processing applications Describes the use of denoising as a pre-processing tool for various signal processing applications or big data analysis Requires only a fundamental knowledge of digital signal processing Includes access to a companion website with source codes, exercises, and additional resourcesDigital Image Denoising in MATLAB is an excellent textbook for undergraduate courses in digital image processing, recognition, and statistical signal processing, and a highly useful reference for researchers and engineers working with digital images, digital video, and other applications requiring denoising techniques.

Presents a review of image denoising algorithms with practical MATLAB implementation guidance

Digital Image Denoising in MATLAB provides a comprehensive treatment of digital image denoising, containing a variety of techniques with applications in high-quality photo enhancement as well as multi-dimensional signal processing problems such as array signal processing, radar signal estimation and detection, and more. Offering systematic guidance on image denoising in theories and in practice through MATLAB, this hands-on guide includes practical examples, chapter summaries, analytical and programming problems, computer simulations, and source codes for all algorithms discussed in the book.

The book explains denoising algorithms including linear and nonlinear filtering, Wiener filtering, spatially adaptive and multi-channel processing, transform and wavelet domains processing, singular value decomposition, and various low variance optimization and low rank processing techniques. Throughout the text, the authors address the theory, analysis, and implementation of the denoising algorithms to help readers solve their image processing problems and develop their own solutions.

Explains how the quality of an image can be quantified in MATLAB Discusses what constitutes a “naturally looking” image in subjective and analytical terms Presents denoising techniques for a wide range of digital image processing applications Describes the use of denoising as a pre-processing tool for various signal processing applications or big data analysis Requires only a fundamental knowledge of digital signal processing Includes access to a companion website with source codes, exercises, and additional resources

Digital Image Denoising in MATLAB is an excellent textbook for undergraduate courses in digital image processing, recognition, and statistical signal processing, and a highly useful reference for researchers and engineers working with digital images, digital video, and other applications requiring denoising techniques.

Presents a review of image denoising algorithms with practical MATLAB implementation guidance

Digital Image Denoising in MATLAB provides a comprehensive treatment of digital image denoising, containing a variety of techniques with applications in high-quality photo enhancement as well as multi-dimensional signal processing problems such as array signal processing, radar signal estimation and detection, and more. Offering systematic guidance on image denoising in theories and in practice through MATLAB, this hands-on guide includes practical examples, chapter summaries, analytical and programming problems, computer simulations, and source codes for all algorithms discussed in the book.

The book explains denoising algorithms including linear and nonlinear filtering, Wiener filtering, spatially adaptive and multi-channel processing, transform and wavelet domains processing, singular value decomposition, and various low variance optimization and low rank processing techniques. Throughout the text, the authors address the theory, analysis, and implementation of the denoising algorithms to help readers solve their image processing problems and develop their own solutions.

Explains how the quality of an image can be quantified in MATLAB Discusses what constitutes a “naturally looking” image in subjective and analytical terms Presents denoising techniques for a wide range of digital image processing applications Describes the use of denoising as a pre-processing tool for various signal processing applications or big data analysis Requires only a fundamental knowledge of digital signal processing Includes access to a companion website with source codes, exercises, and additional resources

Digital Image Denoising in MATLAB is an excellent textbook for undergraduate courses in digital image processing, recognition, and statistical signal processing, and a highly useful reference for researchers and engineers working with digital images, digital video, and other applications requiring denoising techniques.