VDSP++打開。This directory contains an example ADSP-BF537 RTC project that does a basic blink routine and then puts the part in deep sleep mode to be woken up from a RTC Stopwatch Event. Once woken up, the RTC is reconfigured to toggle the EZ KIT LEDs using RTC second, minute, hour, and day interrupts.
標(biāo)簽： directory contains ADSP-BF example
上傳時間： 2015-12-29
上傳用戶：330402686
In this article, we present an overview of methods for sequential simulation from posterior distributions. These methods are of particular interest in Bayesian filtering for discrete time dynamic models that are typically nonlinear and non-Gaussian. A general importance sampling framework is developed that unifies many of the methods which have been proposed over the last few decades in several different scientific disciplines. Novel extensions to the existing methods are also proposed.We showin particular how to incorporate local linearisation methods similar to those which have previously been employed in the deterministic filtering literature these lead to very effective importance distributions. Furthermore we describe a method which uses Rao-Blackwellisation in order to take advantage of the analytic structure present in some important classes of state-space models. In a final section we develop algorithms for prediction, smoothing and evaluation of the likelihood in dynamic models.
標(biāo)簽： sequential simulation posterior overview
上傳時間： 2015-12-31
上傳用戶：225588
Boosting is a meta-learning approach that aims at combining an ensemble of weak classifiers to form a strong classifier. Adaptive Boosting (Adaboost) implements this idea as a greedy search for a linear combination of classifiers by overweighting the examples that are misclassified by each classifier. icsiboost implements Adaboost over stumps (one-level decision trees) on discrete and continuous attributes (words and real values). See http://en.wikipedia.org/wiki/AdaBoost and the papers by Y. Freund and R. Schapire for more details [1]. This approach is one of most efficient and simple to combine continuous and nominal values. Our implementation is aimed at allowing training from millions of examples by hundreds of features in a reasonable time/memory.
標(biāo)簽： meta-learning classifiers combining Boosting
上傳時間： 2016-01-30
上傳用戶：songnanhua
A detailed explanation of C# 2.0 An introduction to Visual Studio 2005, a tool set for building Windows and web applications More than 200 questions and programming exercises to help you better judge your understanding of the material A greater emphasis on event handling Information on generics and generic collections
標(biāo)簽： introduction explanation detailed building
上傳時間： 2013-12-14
上傳用戶：愛死愛死
On Sunday, April 27, 2003, Fresno will celebrate Earth Day in downtown Fresno at Courthouse Park. The event will begin at noon. This year we will include music, speakers, and vendors, plus activities for children. Fresno Earth Day is recognized as the only Earth Day festival that happens in Fresno, and the largest in the Central Valley. The Fresno Earth Day Committee is a small group of environmental activists hoping to broaden the appeal of a better planet and environment. We are a non-profit organization whose fiscal fiduciary is the Fresno Center for Nonviolence.
標(biāo)簽： Fresno Courthouse celebrate downtown
上傳時間： 2016-02-24
上傳用戶：cursor
// algo3-12.cpp 銀行業(yè)務(wù)模擬。實現(xiàn)算法3.6、3.7的程序 #define Qu 4 // 客戶隊列數(shù) #define Khjg 5 // 兩相鄰到達(dá)的客戶的時間間隔最大值 #define Blsj 30 // 每個客戶辦理業(yè)務(wù)的時間最大值 #include"c1.h" typedef struct // 定義ElemType為結(jié)構(gòu)體類型 { int OccurTime // 事件發(fā)生時刻 int NType // 事件類型，Qu表示到達(dá)事件,0至Qu-1表示Qu個窗口的離開事件 }Event,ElemType // 事件類型，有序鏈表LinkList的數(shù)據(jù)元素類型
標(biāo)簽： define algo Khjg 3.6
上傳時間： 2016-03-03
上傳用戶：jcljkh
Fast settling-time added to the already conflicting requirements of narrow channel spacing and low phase noise lead to Fractional4 divider techniques for PLL synthesizers. We analyze discrete "beat-note spurious levels from arbitrary modulus divide sequences including those from classic accumulator methods.
標(biāo)簽： settling-time requirements conflicting already
上傳時間： 2016-04-14
上傳用戶：liansi
Probability distribution functions. estimation - (dir) Probability distribution estimation. dsamp - Generates samples from discrete distribution. erfc2 - Normal cumulative distribution function. gmmsamp - Generates sample from Gaussian mixture model. gsamp - Generates sample from Gaussian distribution. cmeans - C-means (or K-means) clustering algorithm. mahalan - Computes Mahalanobis distance. pdfgauss - Computes probability for Gaussian distribution. pdfgmm - Computes probability for Gaussian mixture model. sigmoid - Evaluates sigmoid function.
標(biāo)簽： distribution Probability estimation functions
上傳時間： 2016-04-28
上傳用戶：13188549192
Image Compression A collection of simple routines for image compression using different techniques. 圖象壓縮的不同方法 BTCODE: Image compression Using Block Truncation Coding. PYRAMID: Image compression based on Gaussian Pyramids. DCTCOMPR: Image compression based on Discrete Cosine Transform. IMCOMPR: Image compression based on Singular Value Decomposition. The given codes can be also used in 2D noise suppression. Notes: The function "conv2fft" performs a 2D FFT-based convolution. Type "help conv2fft" on Matlab command window for more informations.
標(biāo)簽： Compression compression collection different
上傳時間： 2016-05-11
上傳用戶：磊子226
Abstract Based on the demand analysis of the RFID middleware，it suggests how to develop the RFID middle— ware，including the functionality and the mechanism of the event handle，and prospects the future of the RFID mid— dleware．
標(biāo)簽： middleware the Abstract analysis
上傳時間： 2013-12-21
上傳用戶：qilin
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