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Switched-Current Design and Implementation of Oversampling A/D Converters discusses the switched-current (SI) technique and its application in oversampling A/D converters design. The SI technique is an analog sampled-data technique that fully exploits the digital CMOS process. Compared with the traditional switched-capacitor (SC) technique, the SI technique has both pros and cons that are highlighted in the book. With the consideration of similarity and difference of SI and SC techniques, oversampling A/D converter architectures are tailored and optimized for SI design and implementation in the book. Switched-Current Design and Implementation of Oversampling A/D Converters emphasizes the practical aspects of SI circuits without tedious mathematical derivations, and is full of circuit design and implementation examples. There are more than 10 different chips included in the book, demonstrating the high-speed (over 100 MHz) and ultra-low-voltage (1.2 V) operation of SI circuits and systems in standard digital CMOS processes. Therefore, the book is of special value as a practical guide for designing SI circuits and SI oversampling A/D converters. Switched-Current Design and Implementation of Oversampling A/D Converters serves as an excellent reference for analog designers, especially A/D converter designers, and is of interest to digital designers for real-time signal processing who need A/D interfaces. The book may also be used as a text for advanced courses on the subject.
Switched-Current Design and Implementation of Oversampling A/D Converters discusses the switched-current (SI) technique and its application in oversampling A/D converters design. The SI technique is an analog sampled-data technique that fully exploits the digital CMOS process. Compared with the traditional switched-capacitor (SC) technique, the SI technique has both pros and cons that are highlighted in the book. With the consideration of similarity and difference of SI and SC techniques, oversampling A/D converter architectures are tailored and optimized for SI design and implementation in the book. Switched-Current Design and Implementation of Oversampling A/D Converters emphasizes the practical aspects of SI circuits without tedious mathematical derivations, and is full of circuit design and implementation examples. There are more than 10 different chips included in the book, demonstrating the high-speed (over 100 MHz) and ultra-low-voltage (1.2 V) operation of SI circuits and systems in standard digital CMOS processes. Therefore, the book is of special value as a practical guide for designing SI circuits and SI oversampling A/D converters. Switched-Current Design and Implementation of Oversampling A/D Converters serves as an excellent reference for analog designers, especially A/D converter designers, and is of interest to digital designers for real-time signal processing who need A/D interfaces. The book may also be used as a text for advanced courses on the subject.
Switched-Current Signal Processing and A/D Conversion Circuits: Design and Implementation describes the design and implementation of switched-current (SI) circuits with emphasis on signal processing and data-conversion applications. The work includes theoretical analysis, high-level and circuit-level simulation results as well as measurement results from a few of the author's circuit implementations. An extensive overview of the SI field of research is also given. The book contains an extensive overview of the switched-current field of research, and can therefore be used as a quick-reference to the field. The description of each design example has been organized to describe the entire design flow from system level design and simulation, to circuit simulation, layout and measurement as accurately as possible. Thus it is possible to follow each step in the design process. Switched-Current Signal Processing and A/D Conversion Circuits: Design and Implementation is an invaluable reference for researchers and circuit designers working with one-chip mixed-signal system solutions, and low-voltage analog CMOS design. It will also be appreciated by anyone requiring a quick overview of what has been done in the SI field.
Dynamic Translinear and Log-Domain Circuits: Analysis and Synthesis covers both the analysis and synthesis of translinear circuits. The theory is presented using one unifying framework for both static and dynamic translinear networks, which is based on a current-mode approach. General analysis methods are presented, including the large-signal and non-stationary analysis of noise. A well-structured synthesis method is described greatly enhancing the designability of log-domain and translinear circuits. Comparisons are made with respect to alternative analysis and synthesis methods presented in the literature. The theory is illustrated and verified by various examples and realizations.
Neuromorphic Systems Engineering: Neural Networks in Silicon emphasizes three important aspects of this exciting new research field. The term neuromorphic expresses relations to computational models found in biological neural systems, which are used as inspiration for building large electronic systems in silicon. By adequate engineering, these silicon systems are made useful to mankind. Neuromorphic Systems Engineering: Neural Networks in Silicon provides the reader with a snapshot of neuromorphic engineering today. It is organized into five parts viewing state-of-the-art developments within neuromorphic engineering from different perspectives. Neuromorphic Systems Engineering: Neural Networks in Silicon provides the first collection of neuromorphic systems descriptions with firm foundations in silicon. Topics presented include: large scale analog systems in silicon neuromorphic silicon auditory (ear) and vision (eye) systems in silicon learning and adaptation in silicon merging biology and technology micropower analog circuit design analog memory analog interchipcommunication on digital buses £/LIST£ Neuromorphic Systems Engineering: Neural Networks in Silicon serves as an excellent resource for scientists, researchers and engineers in this emerging field, and may also be used as a text for advanced courses on the subject.
Learning on Silicon combines models of adaptive information processing in the brain with advances in microelectronics technology and circuit design. The premise is to construct integrated systems not only loaded with sufficient computational power to handle demanding signal processing tasks in sensory perception and pattern recognition, but also capable of operating autonomously and robustly in unpredictable environments through mechanisms of adaptation and learning. This edited volume covers the spectrum of Learning on Silicon in five parts: adaptive sensory systems, neuromorphic learning, learning architectures, learning dynamics, and learning systems. The 18 chapters are documented with examples of fabricated systems, experimental results from silicon, and integrated applications ranging from adaptive optics to biomedical instrumentation. As the first comprehensive treatment on the subject, Learning on Silicon serves as a reference for beginners and experienced researchers alike. It provides excellent material for an advanced course, and a source of inspiration for continued research towards building intelligent adaptive machines.
Analog integrated circuits are very important as interfaces between the digital parts of integrated electronic systems and the outside world. A large portion of the effort involved in designing these circuits is spent in the layout phase. Whereas the physical design of digital circuits is automated to a large extent, the layout of analog circuits is still a manual, time-consuming and error-prone task. This is mainly due to the continuous nature of analog signals, which causes analog circuit performance to be very sensitive to layout parasitics. The parasitic elements associated with interconnect wires cause loading and coupling effects that degrade the frequency behaviour and the noise performance of analog circuits. Device mismatch and thermal effects put a fundamental limit on the achievable accuracy of circuits. For successful automation of analog layout, advanced place and route tools that can handle these critical parasitics are required. In the past, automatic analog layout tools tried to optimize the layout without quantifying the performance degradation introduced by layout parasitics. Therefore, it was not guaranteed that the resulting layout met the specifications and one or more layout iterations could be needed. In Analog Layout Generation for Performance and Manufacturability, the authors propose a performance driven layout strategy to overcome this problem. In this methodology, the layout tools are driven by performance constraints, such that the final layout, with parasitic effects, still satisfies the specifications of the circuit. The performance degradation associated with an intermediate layout solution is evaluated at runtime using predetermined sensitivities. In contrast with other performance driven layout methodologies, the tools proposed in this book operate directly on the performance constraints, without an intermediate parasitic constraint generation step. This approach makes a complete and sensible trade-off between the different layout alternatives possible at runtime and therefore eliminates the possible feedback route between constraint derivation, placement and layout extraction. Besides its influence on the performance, layout also has a profound impact on the yield and testability of an analog circuit. In Analog Layout Generation for Performance and Manufacturability, the authors outline a new criterion to quantify the detectability of a fault and combine this with a yield model to evaluate the testability of an integrated circuit layout. They then integrate this technique with their performance driven routing algorithm to produce layouts that have optimal manufacturability while still meeting their performance specifications. Analog Layout Generation for Performance and Manufacturability will be of interest to analog engineers, researchers and students.
Highly Linear Integrated Wideband Amplifiers: Design and Analysis Techniques for Frequencies from Audio to RF deals with the complicated issues involved in the design of high-linearity integrated wideband amplifiers for different operating frequencies. The book demonstrates these principles using a number of high-performance designs. New topologies for high linearity are presented, as well as a novel method for estimating the intermodulation distortion of a wideband signal. One of the most exciting results presented is an enhanced feedback configuration called feedback boosting that is capable of very low distortion. Also important is a statistical method for relating the intermodulation distortion of a wideband signal to the total harmonic distortion (THD) of a single tone. The THD, as opposed to the intermodulation distortion of the wideband signal, is easy to measure and use as a design parameter. Three different applications where high linearity is needed are identified, namely audio power amplifiers, wideband IF amplifiers and RF power amplifiers. For these applications high-performance integrated amplifier designs using novel topologies are presented together with measurement results. The audio amplifiers are built in CMOS and are capable of driving 8Omega loudspeaker loads directly without using any external components. One of the designs can operate on a supply voltage down to 1.5V. Both bipolar and CMOS wideband IF amplifiers are built; they are fully differential and have linearity from DC to 20 MHz. Finally, an RF power amplifier is built in CMOS, without using inductors, in order to investigate what performance can be achieved without them. Highly Linear Integrated Wideband Amplifiers: Design and Analysis Techniques for Frequencies from Audio to RF is an excellent reference for researchers and designers of integrated amplifiers, and may be used as a text for advanced courses on the topic.
CMOS Data Converters for Communications distinguishes itself from other data converter books by emphasizing system-related aspects of the design and frequency-domain measures. It explains in detail how to derive data converter requirements for a given communication system (baseband, passband, and multi-carrier systems). The authors also review CMOS data converter architectures and discuss their suitability for communications. The rest of the book is dedicated to high-performance CMOS data converter architecture and circuit design. Pipelined ADCs, parallel ADCs with an improved passive sampling technique, and oversampling ADCs are the focus for ADC architectures, while current-steering DAC modeling and implementation are the focus for DAC architectures. The principles of the switched-current and the switched-capacitor techniques are reviewed and their applications to crucial functional blocks such as multiplying DACs and integrators are detailed. The book outlines the design of the basic building blocks such as operational amplifiers, comparators, and reference generators with emphasis on the practical aspects. To operate analog circuits at a reduced supply voltage, special circuit techniques are needed. Low-voltage techniques are also discussed in this book. CMOS Data Converters for Communications can be used as a reference book by analog circuit designers to understand the data converter requirements for communication applications. It can also be used by telecommunication system designers to understand the difficulties of certain performance requirements on data converters. It is also an excellent resource to prepare analog students for the new challenges ahead.
This chapter presents a set of introductory material, which in addition to providing a general view on the topic, highlights the importance of research in this area. It also presents a short history of the design of smart vision sensors, and points out some of the fundamental issues in the design of such sensors. 1. 1 A General Overview Machine vision is one of the main branches of artificial intelligence. The richness of information present in images makes them the first choice as an input to an artificial system which tries to interact with its environment. A large proportion of the brain of many advanced species is dedicated to visual information processing, which illustrates the importance of visual information in biological systems. Biological visual systems have evolved over millions of years, and each specie has developed a specialized visual system tailored for the essential tasks of survival, such as catching a prey, or escaping a predator. Implementing electronic hardware for image processing, therefore, may benefit from the underlying fundamental aspects of biological vision, though in no respect should this be regarded as a solid framework for electronic vision systems. Traditionally, computer vision algorithms are performed on images captured by conventional cameras, and processing is accomplished by means of general purpose digital computers. More advanced systems utilize dedicated hardware to speed up the processing stage.