Simulated annealing GAs suffer from shortcomings such as insufficient search efficiency and premature convergence. We now propose an improved adaptive simulated annealing GA that possesses better search efficiency and...
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Simulated annealing GAs suffer from shortcomings such as insufficient search efficiency and premature convergence. We now propose an improved adaptive simulated annealing GA that possesses better search efficiency and the capability to converge to good global optimum even for high-dimensional complex functions. The description of traditional simulated annealing GAs and proposed adaptive simulated annealing GA and the six characteristics of traditional simulated annealing GAs are described. The proposed adaptive simulated annealing GA is described and cross probability and mutation probability of the proposed algorithm are selected adaptively for enhancing algorithm stability and convergence. The proof of our theorem for the convergence of the proposed adaptive simulated annealing GA is also presented, which is rather lengthy and takes up more space. Finally, for comparing our proposed algorithm with traditional simulated annealing GAs and the improved evolutionary programming algorithm, we give a numerical simulation example. These results demonstrate the effectiveness and efficiency of the proposed algorithm as applied to high-dimensional complex functions and its performances are better than those of traditional simulated annealing GAs and the improved evolutionary programming algorithm.
This paper presents a novel face recognition method based on complete Kernel Fisher discriminant (CKFD) analysis of Gabor features with power polynomial models. By integrating the Gabor wavelet representation of face ...
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This paper presents a novel face recognition method based on complete Kernel Fisher discriminant (CKFD) analysis of Gabor features with power polynomial models. By integrating the Gabor wavelet representation of face images and the enhanced powerful discriminator named CKFD analysis, the method is robust to changes in illumination and facial expressions and poses. On the other hand, the extended polynomial Kernels, namely fractional power polynomial (FPP) models, are employed in CKFD analysis, which enhance face recognition performance. Comparing with existing PCA, LDA, KPCA, KFD and CKFD methods, the proposed method gives superior results in the ORL and Yale face databases. Its good performance in the two face databases gives the promising idea to solve the pose, illumination, and expression (PIE) problem of face recognition
Based on Perception Linear Prediction (PLP), an approach to extract features from underwater target signal is presented. The method is the simulation of hearing property of human beings. Through the auditory psycholog...
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Based on Perception Linear Prediction (PLP), an approach to extract features from underwater target signal is presented. The method is the simulation of hearing property of human beings. Through the auditory psychology, three auditory spectrums are estimated, and they are Critical band, Equal-loudness curve and Intensity-loudness power. Then, a twelve-dimension feature vector is obtained. The vector is also a twelve-order all-pole model and it is robust. With the feature vector, the training and recognition processes are performed. The real sea experiments prove that human ear is at different level of sensitivity with different frequency bands where six kinds of radiated noises exist respectively, that the underwater target features are robust, that the dimension is relatively lower and the computation is less expensive and the recognition ratio may arrive 91% to six kinds of underwater target noise.
The goal of this book is to explain elementary programming concepts such as loops, abstractions, composition, and conditionals to novices of all ages. It teaches the core programming concepts based on simple problems,...
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ISBN:
(数字)9781430200376
ISBN:
(纸本)9781590594919
The goal of this book is to explain elementary programming concepts such as loops, abstractions, composition, and conditionals to novices of all ages. It teaches the core programming concepts based on simple problems, involving the manipulation of robots or "turtles" as frequently seen in school learning environments. The ideal reader wants to have fun programming. And the reader does not have to be fluent in any programming language before they pick up this book. The chapters of this book are relatively small. The idea is that each chapter can be turned into a one or two hour lab session. This book creates a path to teach object-oriented programming and promote the encapsulation of data, but most readers will simply appreciate the delightful sequence of fun and easy-to-do exercises with a robot/turtle
This paper proposes a density based clustering algorithm which takes obstacles into consideration. The proposed Clustering with Obstacle Entities algorithm COE-DBSCAN is based on the DBSCAN algorithm, which performs e...
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This paper shows the impact of the atomic capabilities concept to include control-oriented knowledge of linear control systems in the decisions making structure of physical agents. These agents operate in a real envir...
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作者：
Maciej NiedzwieckiAdam SobocinskiFaculty of Electronics
Telecommunications and Computer Science Department of Automatic Control Gdansk University of Technology Narutowicza 11/12 Gdansk Poland Tel: + 48 58 3472519 Fax: +48 58 3416132 e-mail: maciekn@eti.pg.gda.pl adsob@eti.pg.
Generalized adaptive notch filters are used for identification/ tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. Belon...
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Generalized adaptive notch filters are used for identification/ tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. Belonging to the class of causal adaptive filters, the generalized adaptive notch filtering algorithms yield biased frequency estimates. We show that this bias can be removed, or at least substantially reduced. The only price paid for the resulting improvement of the filter’s tracking performance is in terms of a decision delay, which must be incorporated in the adaptive loop. Since decision delay is acceptable in many practical applications, the proposed bias/delay trade-off is an attractive alternative to the classical bias/variance compromise.
This paper introduces a new technique to design applicable one-point feedback controllers for distributed parameter systems (DPS) with uncertainty. The technique is an extension of the Quantitative Feedback Theory (QF...
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This paper presents a conversational interface that uses the speech recognition and synthesis and animation abilities of two Microsoft software agents in order to assure a more natural and efficient interface with an ...
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Decision trees have been found very effective for classification especially in data mining. Although classification is a well studied problem, most of the current classification algorithms need an in-memory data struc...
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