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of SAX/GA and genetic operators work to optimize possible solutions. This study is later used as the baseline for the development of parallel;
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functions and appearances. Pattern discovery is thus important for deciphering gene regulation, which has tremendous impacts on the understanding;
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High Performance Deformable Image Registration Algorithms for Manycore Processors develops highly data-parallel image registration;
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presented in Genetic Algorithms for Pattern Recognition makes it a unique text, ideal for graduate students and researchers.;
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presented in Genetic Algorithms for Pattern Recognition makes it a unique text, ideal for graduate students and researchers.;
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Obstacle Avoidance in Multi-robot Systems: Experiments in Parallel Genetic Algorithms offers a novel framework for solving the path;
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definitions about patterns, patterns mining, type of patterns and the usefulness of patterns in the knowledge discovery process. As it is described;
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analyze their complexity for GPUs. Part VI: Applications and Related Topics provides use cases and examples of how GPUs are used across many;
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Algorithms (GAs). The authors explain and demonstrate the validity of these cellular genetic algorithms throughout the book with equal and parallel;
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Nowadays, GPUs are multi-core parallel processors with very high memory bandwidth. Recently for last few years developers and researchers;
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in Evolutionary Optimization Pattern Discovery, Pattern Recognition, and System Identification.- Hierarchical Levels of Learning.- Self-Adaptation;
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and applications: graphics processing units (GPUs) for general-purpose computing (GPGPU) and swarm intelligence. This book not only presents;
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discussed include distributed branch-and-bound algorithms, parallel genetic algorithms for large scale discrete problems, simulated annealing;
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discussion on Metaheuristics and Parallelism Part Two: Parallel Metaheuristic Models, including Parallel Genetic Algorithms, Parallel Genetic;
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such as CUDA libraries. The authors share their experience developing algorithms using MATLAB, C++ and GPUs for huge datasets, modifying MATLAB;
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This book presents the complex topic of using computational intelligence for pattern recognition in a straightforward and applicable way;
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Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both;
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Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both;
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Authoritative coverage of a revolutionary technique for overcoming problems in electromagnetic design Genetic algorithms are stochastic;
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Kernel methods provide a powerful and unified framework for pattern discovery, motivating algorithms that can act on general types of data;
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models using Python libraries such as DEAP, scikit-learn, and NumPy Key Features Explore the ins and outs of genetic algorithms with this fast;
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of molecular genetic mechanisms of pattern formation, mutations in axial patterning, genetic regulation of growth, and more using the Drosophila eye as;
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of molecular genetic mechanisms of pattern formation, mutations in axial patterning, genetic regulation of growth, and more using the Drosophila eye as;
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Reviews FPGA architecture and programming Presents several parallel algorithms for computing alignments on the Cell/BE architecture;
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Get a hands-on introduction to machine learning with genetic algorithms using Python. Step-by-step tutorials build your skills from Hello;
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This book describes a new pattern discovery approach based on the combination among rules between Perceptually Important Points (PIPs) and;
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This book describes the methods and algorithms for image pre-processing and recognition. These methods are based on a parallel shift;
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