Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

In this paper, we intend to formulate a new meta-heuristic algorithm, called Cuckoo Search (CS), for solving optimization problems. This algorithm is based on the obligate brood parasitic behaviour of some cuckoo species in combination with the Levy flight behaviour of some birds and fruit flies. We validate the proposed algorithm against test functions and then compare its performance with those of genetic algorithms and particle swarm optimization. Finally, we discuss the implication of the results and suggestion for further research.

Cuckoo Search via Lévy flights

Nature-inspired algorithms are among the most powerful algorithms for optimization. This paper intends to provide a detailed description of a new Firefly Algorithm (FA) for multimodal optimization applications. We will compare the proposed firefly algorithm with other metaheuristic algorithms such as particle swarm optimization (PSO). Simulations and results indicate that the proposed firefly algorithm is superior to existing metaheuristic algorithms. Finally we will discuss its applications and implications for further research.

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Firefly algorithms for multimodal optimization

It is shown that, particularly for terrestrial cellular telephony, the interference-suppression feature of CDMA (code division multiple access) can result in a many-fold increase in capacity over analog and even over competing digital techniques. A single-cell system, such as a hubbed satellite network, is addressed, and the basic expression for capacity is developed. The corresponding expressions for a multiple-cell system are derived. and the distribution on the number of users supportable per cell is determined. It is concluded that properly augmented and power-controlled multiple-cell CDMA promises a quantum increase in current cellular capacity. >

On the capacity of a cellular CDMA system

A unified view of metaheuristics This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking and bioinformatics to engineering design, routing, and scheduling. It presents the main design questions for all families of metaheuristics and clearly illustrates how to implement the algorithms under a software framework to reuse both the design and code. Throughout the book, the key search components of metaheuristics are considered as a toolbox for: Designing efficient metaheuristics (e.g. local search, tabu search, simulated annealing, evolutionary algorithms, particle swarm optimization, scatter search, ant colonies, bee colonies, artificial immune systems) for optimization problems Designing efficient metaheuristics for multi-objective optimization problems Designing hybrid, parallel, and distributed metaheuristics Implementing metaheuristics on sequential and parallel machines Using many case studies and treating design and implementation independently, this book gives readers the skills necessary to solve large-scale optimization problems quickly and efficiently. It is a valuable reference for practicing engineers and researchers from diverse areas dealing with optimization or machine learning; and graduate students in computer science, operations research, control, engineering, business and management, and applied mathematics.

/pdf/metaheuristics-from-design-to-implementation-1vqdfv8nk9.pdf

Metaheuristics: From Design to Implementation

Fuzzy logic, neural networks, and evolutionary computation are the core methodologies of soft computing (SC). SC is causing a paradigm shift in engineering and science fields since it can solve problems that have not been able to be solved by traditional analytic methods. In addition, SC yields rich knowledge representation, flexible knowledge acquisition, and flexible knowledge processing, which enable intelligent systems to be constructed at low cost. This paper reviews applications of SC in several industrial fields to show the various innovations by TR, HMIQ, and low cost in industries that have been made possible by the use of SC. Our paper intends to remove the gap between theory and practice and attempts to learn how to apply soft computing practically to industrial systems from examples/analogy, reviewing many application papers.

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Industrial applications of soft computing: a review

A simple combination of nonlinear and linear digital signal processing methods is proposed for efficient noise reduction in zero crossing detectors. The method is very robust against strong impulsive noise, typically encountered in thyristor power converters, where reliable zero crossing detection is required for firing synchronization. A systematic design procedure is described for the proposed filter-based synchronization method, taking into account the specified line frequency tolerance. The fully digital signal processing approach allows compact implementations, and supports flexible interfacing to digital motor control systems. >

Noise reduction in zero crossing detection by predictive digital filtering

This paper gives a review of sensors, methods, and algorithms available for the measurement of angular acceleration. The emphasis is in delay-sensitive, real-time applications. Although the angular acceleration can be measured indirectly using either a rotating angle sensor or a velocity sensor, the noise-amplification problem related to the differentiation process has motivated the efforts to develop transducers for direct sensing of angular acceleration. Direct measuring of linear acceleration is widely in everyday use, but the angular acceleration sensors, particularly those with unlimited rotation angle, can still be considered as emerging devices. Consequently, there exist two principal challenges for the research and development community: to develop economical and accurate angular accelerometers with unlimited rotation range, and to create wideband indirect techniques with small lag and high signal-to-error ratio.

Angular acceleration measurement: a review

The leading text in the field explains step by step how to write software that responds in real timeFrom power plants to medicine to avionics, the world increasingly depends on computer systems that can compute and respond to various excitations in real time. The Fourth Edition of Real-Time Systems Design and Analysis gives software designers the knowledge and the tools needed to create real-time software using a holistic, systems-based approach. The text covers computer architecture and organization, operating systems, software engineering, programming languages, and compiler theory, all from the perspective of real-time systems design.The Fourth Edition of this renowned text brings it thoroughly up to date with the latest technological advances and applications. This fully updated edition includes coverage of the following concepts:Multidisciplinary design challengesTime-triggered architecturesArchitectural advancementsAutomatic code generationPeripheral interfacingLife-cycle processesThe final chapter of the text offers an expert perspective on the future of real-time systems and their applications.The text is self-contained, enabling instructors and readers to focus on the material that is most important to their needs and interests. Suggestions for additional readings guide readers to more in-depth discussions on each individual topic. In addition, each chapter features exercises ranging from simple to challenging to help readers progressively build and fine-tune their ability to design their own real-time software programs.Now fully up to date with the latest technological advances and applications in the field, Real-Time Systems Design and Analysis remains the top choice for students and software engineers who want to design better and faster real-time systems at minimum cost.

Seppo J. Ovaska

Papers

Industrial applications of soft computing: a review

Noise reduction in zero crossing detection by predictive digital filtering

Angular acceleration measurement: a review

Real-Time Systems Design and Analysis : Tools for the Practitioner

A general framework for statistical performance comparison of evolutionary computation algorithms