％ EM algorithm for k multidimensional Gaussian mixture estimation ％ ％ Inputs: ％ X(n,d) - input data, n=number of observations, d=dimension of variable ％ k - maximum number of Gaussian components allowed ％ ltol - percentage of the log likelihood difference between 2 iterations ([] for none) ％ maxiter - maximum number of iteration allowed ([] for none) ％ pflag - 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none) ％ Init - structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none) ％ ％ Ouputs: ％ W(1,k) - estimated weights of GM ％ M(d,k) - estimated mean vectors of GM ％ V(d,d,k) - estimated covariance matrices of GM ％ L - log likelihood of estimates ％
標(biāo)簽： multidimensional estimation algorithm Gaussian
上傳時(shí)間： 2013-12-03
上傳用戶：我們的船長
GloptiPoly 3: moments, optimization and semidefinite programming. Gloptipoly 3 is intended to solve, or at least approximate, the Generalized Problem of Moments (GPM), an infinite-dimensional optimization problem which can be viewed as an extension of the classical problem of moments [8]. From a theoretical viewpoint, the GPM has developments and impact in various areas of mathematics such as algebra, Fourier analysis, functional analysis, operator theory, probability and statistics, to cite a few. In addition, and despite a rather simple and short formulation, the GPM has a large number of important applications in various fields such as optimization, probability, finance, control, signal processing, chemistry, cristallography, tomography, etc. For an account of various methodologies as well as some of potential applications, the interested reader is referred to [1, 2] and the nice collection of papers [5].
標(biāo)簽： optimization semidefinite programming GloptiPoly
上傳時(shí)間： 2016-06-05
上傳用戶：lgnf
％ decode with soft-input viterbi algorithm 硬判決 ％ //k=4,r=1/2 ％輸入數(shù)據(jù)為軟信息，并且數(shù)據(jù)為均值為1的BPSK調(diào)制，如果均值為MEAN,那么62,63,103,104行應(yīng)做相應(yīng)修改
標(biāo)簽： soft-input algorithm viterbi decode
上傳時(shí)間： 2014-10-28
上傳用戶：aig85
The package includes 3 Matlab-interfaces to the c-code: 1. inference.m An interface to the full inference package, includes several methods for approximate inference: Loopy Belief Propagation, Generalized Belief Propagation, Mean-Field approximation, and 4 monte-carlo sampling methods (Metropolis, Gibbs, Wolff, Swendsen-Wang). Use "help inference" from Matlab to see all options for usage. 2. gbp_preprocess.m and gbp.m These 2 interfaces split Generalized Belief Propagation into the pre-process stage (gbp_preprocess.m) and the inference stage (gbp.m), so the user may use only one of them, or changing some parameters in between. Use "help gbp_preprocess" and "help gbp" from Matlab. 3. simulatedAnnealing.m An interface to the simulated-annealing c-code. This code uses Metropolis sampling method, the same one used for inference. Use "help simulatedAnnealing" from Matlab.
標(biāo)簽： Matlab-interfaces inference interface the
上傳時(shí)間： 2016-08-27
上傳用戶：gxrui1991
A Module-based Wireless Node (MW-Node) is a Node with wireless and mobile capabilities added by means of modules. It is not a new node object derived from Node. Rather it is a new layout of mostly existing components. Rationale for this new design has been presented in [1]. The MW-Node provides a flexible support for wireless and mobile networking and in particular: support for multiple interfaces/multiple channels, and a common basis for the implementation of wireless routing protocols.
標(biāo)簽： Node Module-based capabilities Wireless
上傳時(shí)間： 2013-12-26
上傳用戶：大三三
Jvm 規(guī)范說明。The Java Virtual Machine was designed to support the Java programming language. Some concepts and vocabulary from the Java language are thus necessary to understand the virtual machine. This chapter gives enough of an overview of Java to support the discussion of the Java Virtual Machine to follow. Its material has been condensed from The Java Language Specification, by James Gosling, Bill Joy, and Guy Steele. For a complete discussion of the Java language, or for details and examples of the material in this chapter, refer to that book. Readers familiar with that book may wish to skip this chapter. Readers familiar with Java, but not with The Java Language Specification, should at least skim this chapter for the terminology it introduces.
標(biāo)簽： Java programming designed language
上傳時(shí)間： 2013-12-19
上傳用戶：wangyi39
After the successful global introduction during the past decade of the second generation (2G) digital mobile communications systems, it seems that the third generation (3G) Universal Mobile Communication System (UMTS) has finally taken off, at least in some regions. The plethora of new services that are expected to be offered by this system requires the development of new paradigms in the way scarce radio resources should be managed. The Quality of Service (QoS) concept, which introduces in a natural way the service differentiation and the possibility of adapting the resource consumption to the specific service requirements, will open the door for the provision of advanced wireless services to the mass market.
標(biāo)簽： the introduction successful generation
上傳時(shí)間： 2013-12-30
上傳用戶：qq21508895
PRINCIPLE: The UVE algorithm detects and eliminates from a PLS model (including from 1 to A components) those variables that do not carry any relevant information to model Y. The criterion used to trace the un-informative variables is the reliability of the regression coefficients: c_j=mean(b_j)/std(b_j), obtained by jackknifing. The cutoff level, below which c_j is considered to be too small, indicating that the variable j should be removed, is estimated using a matrix of random variables.The predictive power of PLS models built on the retained variables only is evaluated over all 1-a dimensions =(yielding RMSECVnew).
標(biāo)簽： from eliminates PRINCIPLE algorithm
上傳時(shí)間： 2016-11-27
上傳用戶：凌云御清風(fēng)
ST uPSD32XX I2C This example demo code is provided as is and has no warranty, implied or otherwise. You are free to use/modify any of the provided code at your own risk in your applications with the expressed limitation of liability (see below) so long as your product using the code contains at least one uPSD products (device)
標(biāo)簽： otherwise provided warranty example
上傳時(shí)間： 2013-12-07
上傳用戶：標(biāo)點(diǎn)符號
neural network utility is a Neural Networks library for the C++ Programmer. It is entirely object oriented and focuses on reducing tedious and confusing problems of programming neural networks. By this I mean that network layers are easily defined. An entire multi-layer network can be created in a few lines, and trained with two functions. Layers can be connected to one another easily and painlessly.
標(biāo)簽： Programmer Networks entirely network
上傳時(shí)間： 2013-12-24
上傳用戶：liuchee
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