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This a large book, and your class will probably cover only a portion of its material. We have tried, however, to make this a book that will be useful to you now as a course textbook and also later in your career as a mathematical desk reference or an engineering handbook

Foreword The four case studies that follow each have a number of common features. They each illustrate the birth of an idea and show how that idea can be realised into a marketable product. Each case study deals with engineering design and development issues and each highlights the importance of dev ...

我用matlab写的一个corner detector, 效果比现在流行的harris，susan，CSS等效果要好。 Algorithm is derived from: X.C. He and N.H.C. Yung, Curvature Scale Space Corner Detector with Adaptive Threshold and Dynamic Region of Support , Proceedings of the 17th International Conference on Pattern Recognition, ...

【下载说明】 这里提供给大家的是《Embedded Linux: Hardware, Software, and Interfacing》（嵌入式 Linux---硬件、软件与接口）一书的英文原版CHM格式下载。 【作者简介】 Craig Hollabaugh has been fascinated by electronics since he bought an AM radio in elementary school. He was first exposed to Unix during ...

On-Line MCMC Bayesian Model Selection This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and deta ...

D-S.Kim, Y.S.Lee, W.H.Kwon, and H.S.Park, "Maximum Allowable Delay Bounds in Networked Control Systems", Control Engineering Practice (Elsvier Science) (Simulation Example - Matlab Code), PP.1301-1313, Vol.11, Issue 11, December, 2003

This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, N ...

This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that n ...

The algorithms are coded in a way that makes it trivial to apply them to other problems. Several generic routines for resampling are provided. The derivation and details are presented in: Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas and Eric Wan. The Unscented Particle Filter. Technical re ...

This white paper describes a collection of standards, conventions, and guidelines for writing solid Java code. They are based on sound, proven software engineering principles that lead to code that is easy to understand, to maintain, and to enhance.