From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

Fundamental and advanced developments in neuro-fuzzy synergisms for modeling and control are reviewed. The essential part of neuro-fuzzy synergisms comes from a common framework called adaptive networks, which unifies both neural networks and fuzzy models. The fuzzy models under the framework of adaptive networks is called adaptive-network-based fuzzy inference system (ANFIS), which possess certain advantages over neural networks. We introduce the design methods for ANFIS in both modeling and control applications. Current problems and future directions for neuro-fuzzy approaches are also addressed. >

https://ir.nctu.edu.tw:443/bitstream/11536/2013/1/A1995QJ99800003.pdf

Neuro-fuzzy modeling and control

Fuzzy logic control was originally introduced and developed as a model free control design approach. However, it unfortunately suffers from criticism of lacking of systematic stability analysis and controller design though it has a great success in industry applications. In the past ten years or so, prevailing research efforts on fuzzy logic control have been devoted to model-based fuzzy control systems that guarantee not only stability but also performance of closed-loop fuzzy control systems. This paper presents a survey on recent developments (or state of the art) of analysis and design of model based fuzzy control systems. Attention will be focused on stability analysis and controller design based on the so-called Takagi-Sugeno fuzzy models or fuzzy dynamic models. Perspectives of model based fuzzy control in future are also discussed

/pdf/a-survey-on-analysis-and-design-of-model-based-fuzzy-control-3hrjlrel0k.pdf

A Survey on Analysis and Design of Model-Based Fuzzy Control Systems

Ten years of genetic fuzzy systems: current framework and new trends

Sliding-mode control (SMC) has been studied extensively for over 50 years and widely used in practical applications due to its simplicity and robustness against parameter variations and disturbances. Despite the extensive research activities carried out, the key technical problems associated with SMC remain as challenging research questions due to demands for new industrial applications and technological advances. In this respect, soft computing (SC) is a rather recent development in intelligent systems which has provided alternative means for adaptive learning and control to overcome the key SMC technical problems. Substantial efforts in integration of SMC with SC have been placed in recent years with various successes. In this paper, we provide the state of the art of recent developments in SMC systems with SC, examining key technical research issues and future perspectives.

Sliding-Mode Control With Soft Computing: A Survey

Mechanical devices usually come with undesirable nonlinearities, such as friction, backlashes, and saturations. Under the assumption of linear systems, the commonly seen identification schemes utilize sinusoidal excitation signals for parameter identification. However, the data needed for identification are unavoidably distorted by the aforementioned nonlinearities and the identification result may not be satisfactory. In the paper, binary test signals are used to perform identification, thus simplifying the behavior of friction. An identification method based on the difference of binary multifrequency excitation signals is proposed. The modified identification algorithm does not suffer from the problem of nonlinear distortions in the signal shape and is able to determine the nonlinear friction such that an accurate servo system model can be derived. A high-precision ball-screw table with asymmetric friction is identified as a test plant for this approach. The results prove that the method can be used very successfully.

Frequency-domain identification algorithms for servo systems with friction

This paper demonstrates a novel approach for enhancing ultrasound-induced heating by the introduction of acoustic cavitation using simultaneous sonication with low- and high-frequency ultrasound. A spherical focused transducer (566 or 1155 kHz) was used to generate the thermal lesions, and a low-frequency planar transducer (40 or 28 kHz) was used to enhance the bubble activity. Ex vivo fresh porcine muscles were used as the target of ultrasound ablation. The emitted signals and the signals backscattered from the bubble activity were also recorded during the heating process by a PVDF-type needle hydrophone, and thermocouples were inserted to measure temperatures. Compared with the lesions formed by a single focused transducer, the size of the lesions generated by this approach were as much as 140% larger along the axial direction and 200% larger along the radial direction for combined 566- and 40-kHz sonication. They were 47% and 66% larger along the axial and radial directions, respectively, for combined 1155- and 28-kHz sonication. Cavitation activities enhanced by low-frequency ultrasound were confirmed by the presence of subharmonics in the spectrum and temperature increase as a result of increased tissue absorption. These observations imply that cavitation-enhanced lesions can be generated without reducing the penetration ability; they also show the advantage of producing larger and more uniform thermal lesions by multiple sonications. This technique provides an easy and effective way to achieve cavitation-enhanced heating, and may be useful for generating large and deep-seated thermal lesions.

/pdf/cavitation-enhanced-ultrasound-thermal-therapy-by-combined-3m3d3svqfg.pdf

Cavitation-enhanced ultrasound thermal therapy by combined low- and high-frequency ultrasound exposure

Design of self-learning fuzzy sliding mode controllers based on genetic algorithms

An adaptive fuzzy sliding mode controller (AFSMC) is proposed. The parameters of the membership functions in the fuzzy rule base are changed according to some adaptive algorithm for the purpose of controlling the system state to hit a user-defined sliding surface and then slide along it. The initial IF-THEN rules in the AFSMC can be randomly selected or roughly given by human experts, and then automatically tuned by a direct adaptive law. Therefore, the reduction of the expertise dependency in the design procedure of fuzzy logic control is called the rule tolerance property. By applying the AFSMC to control a nonlinear unstable inverted pendulum system, the simulation results showed the expected approximation sliding property, and the dynamic behavior of control system can be determined by the sliding surface. >

/pdf/design-of-adaptive-fuzzy-sliding-mode-for-nonlinear-system-3brn6whfxa.pdf

Design of adaptive fuzzy sliding mode for nonlinear system control

This paper presents a novel single-stage push-pull boost converter with improved integrated magnetics and a better low-ripple input current. Most of the reported single-stage power factor corrected (PFC) rectifiers cascade a boost-type converter with a dc-dc converter. It is found that the push-pull converter, when the duty cycles are greater than 50%, can simplify the front end of the boost-type converter to a novel single-stage converter. Coupled inductor techniques provide a method to reduce the converter size and weight and to achieve a ripple-free current. All the magnetic components including the input filter inductor and the step-down transformer are integrated into a single EI core. The proposed integrated magnetic structure has a simple core structure, a small leakage inductance, and low core losses. The prototype is built to demonstrate the theoretical prediction

/pdf/single-stage-push-pull-boost-converter-with-integrated-4lupc866t7.pdf

Yung-Yaw Chen

Papers

Frequency-domain identification algorithms for servo systems with friction

Cavitation-enhanced ultrasound thermal therapy by combined low- and high-frequency ultrasound exposure

Design of self-learning fuzzy sliding mode controllers based on genetic algorithms

Design of adaptive fuzzy sliding mode for nonlinear system control

Single-Stage Push–Pull Boost Converter With Integrated Magnetics and Input Current Shaping Technique

Yung-Yaw Chen

Papers

Frequency-domain identification algorithms for servo systems with friction

Cavitation-enhanced ultrasound thermal therapy by combined low- and high-frequency ultrasound exposure

Design of self-learning fuzzy sliding mode controllers based on genetic algorithms

Design of adaptive fuzzy sliding mode for nonlinear system control

Single-Stage Push&#8211;Pull Boost Converter With Integrated Magnetics and Input Current Shaping Technique

Single-Stage Push–Pull Boost Converter With Integrated Magnetics and Input Current Shaping Technique