我用matlab寫的一個corner detector, 效果比現(xiàn)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, 2:791-794, August 2004. Improved algorithm has been included in A Corner Detector based on Global and Local Curvature Properties and submitted to Optical Engineering.
標(biāo)簽： detector matlab corner harris
上傳時間： 2013-12-30
上傳用戶：569342831
【下載說明】 這里提供給大家的是《Embedded Linux: Hardware, Software, and Interfacing》（嵌入式 Linux---硬件、軟件與接口）一書的英文原版CHM格式下載。 【作者簡介】 Craig Hollabaugh has been fascinated by electronics since he bought an AM radio in elementary school. He was first exposed to Unix during a cross-country talk session in 1985. Later, he administered networked Sun and DEC workstations while pursuing a doctoral degree in electrical Engineering at Georgia Institute of Technology. 【內(nèi)容提要】 本書通過一個冬季旅游勝地自動化管理項目實例，從軟件、硬件和接口的觀點介紹嵌入式Linux。引入項目需求后，作者講述了開發(fā)環(huán)境的建立，接著用一系列軟硬件接口實例展示了如何使用異步串行通信、PC并口、USB、內(nèi)存I/O、同步串行通信以及中斷，等等。最后介紹了將前面所有的工作有機地組織在一起的系統(tǒng)集成過程。本書以實際應(yīng)用為導(dǎo)向，書中整個項目的實施過程和軟硬件接口實例都具實踐指導(dǎo)意義。
標(biāo)簽： Linux Interfacing Embedded Hardware
上傳時間： 2014-01-22
上傳用戶：shus521
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 details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
標(biāo)簽： demonstrates sequential Selection Bayesian
上傳時間： 2016-04-07
上傳用戶：lindor
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
標(biāo)簽： Allowable Networked Control Maximum
上傳時間： 2016-04-10
上傳用戶：lifangyuan12
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, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
標(biāo)簽： sequential reversible algorithm nstrates
上傳時間： 2014-01-18
上傳用戶：康郎
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 need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar -xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
標(biāo)簽： reversible algorithm the nstrates
上傳時間： 2014-01-08
上傳用戶：cuibaigao
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 report CUED/F-INFENG/TR 380, Cambridge University Department of Engineering, May 2000. After downloading the file, type "tar -xf upf_demos.tar" to uncompress it. This creates the directory webalgorithm containing the required m files. Go to this directory, load matlab5 and type "demo_MC" for the demo.
標(biāo)簽： algorithms problems Several trivial
上傳時間： 2014-01-20
上傳用戶：royzhangsz
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.
標(biāo)簽： conventions collection guidelines describes
上傳時間： 2014-12-08
上傳用戶：hakim
摘自university of waterloo的個別知道筆記，主要關(guān)于electrical and computer Engineering方面，包括了8-bit hamming的編解碼以及使用VHDL的硬件開發(fā)
標(biāo)簽： university waterloo of
上傳時間： 2016-07-07
上傳用戶：qq521
空間桁架的有限元分析源碼，是國外《intrduction to finite elements on Engineering》中的。
上傳時間： 2013-12-09
上傳用戶：Zxcvbnm
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