KMEANS Trains a k means cluster model.CENTRES = KMEANS(CENTRES, DATA, OPTIONS) uses the batch K-means algorithm to set the centres of a cluster model. The matrix DATA represents the data which is being clustered, with each row corresponding to a vector. The sum of squares error function is used. The point at which a local minimum is achieved is returned as CENTRES.
標簽： CENTRES KMEANS OPTIONS cluster
上傳時間： 2014-01-07
上傳用戶：zhouli
aiNet application is a very powerful and a very simple tool for solving the problems which are usually solved with artificial neural networks (ANN). All possible tests we had run proved that the results obtained with aiNet are at least as good as the results obtained with some other ANNs. Let us state some of aiNet抯 features. (c) aiNet 1995-1997
標簽： very application powerful problems
上傳時間： 2014-01-16
上傳用戶：wang5829
This book is for the experience and not the same level of the design process so prepared by the staff, of course, the reader should at least be able to prepare a simple C language program. On the C language are learning readers, this book is any C language tutorial excellent supporting materials, to be able to answer all relevant questions.
標簽： the experience prepared process
上傳時間： 2013-12-20
上傳用戶：jcljkh
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].
標簽： optimization semidefinite programming GloptiPoly
上傳時間： 2016-06-05
上傳用戶：lgnf
ClustanGraphics聚類分析工具。提供了11種聚類算法。 Single Linkage (or Minimum Method, Nearest Neighbor) Complete Linkage (or Maximum Method, Furthest Neighbor) Average Linkage (UPGMA) Weighted Average Linkage (WPGMA) Mean Proximity Centroid (UPGMC) Median (WPGMC) Increase in Sum of Squares (Ward s Method) Sum of Squares Flexible (ß space distortion parameter) Density (or k-linkage, density-seeking mode analysis)
標簽： ClustanGraphics Complete Neighbor Linkage
上傳時間： 2014-01-02
上傳用戶：003030
Jvm 規范說明。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.
標簽： Java programming designed language
上傳時間： 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.
標簽： the introduction successful generation
上傳時間： 2013-12-30
上傳用戶：qq21508895
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)
標簽： otherwise provided warranty example
上傳時間： 2013-12-07
上傳用戶：標點符號
Please carefully read the many features of your package and then write the specific function (at least 20 words). As far as possible not to let the station master of the time spent in the
標簽： carefully the features function
上傳時間： 2013-12-16
上傳用戶：ouyangtongze
In computer vision, sets of data acquired by sampling the same scene or object at different times, or from different perspectives, will be in different coordinate systems. Image registration is the process of transforming the different sets of data into one coordinate system. Registration is necessary in order to be able to compare or integrate the data obtained from different measurements. Image registration is the process of transforming the different sets of data into one coordinate system. To be precise it involves finding transformations that relate spatial information conveyed in one image to that in another or in physical space. Image registration is performed on a series of at least two images, where one of these images is the reference image to which all the others will be registered. The other images are referred to as target images.
標簽： different computer acquired sampling
上傳時間： 2013-12-28
上傳用戶：來茴
