基于現(xiàn)代譜估計方法的間諧波檢測Spectrum estimates based on modern methods of detection of harmonic
標(biāo)簽： estimates detection Spectrum harmonic
上傳時間： 2014-12-20
上傳用戶：qiaoyue
Software testing technology, introduced the common methods of software testing, software testing in the basic test ideas
標(biāo)簽： testing software technology introduced
上傳時間： 2014-01-26
上傳用戶：qiao8960
an analysis software with souce code for the time series with methods based on the theory of nonlinear deterministic dynamical systems, or chaos theory.這套軟件源碼是根據(jù)H. Kantz and T. Schreiber, ``Nonlinear Time Series Analysis , Cambridge University Press, Cambridge (1997).
標(biāo)簽： with the analysis software
上傳時間： 2013-12-10
上傳用戶：ve3344
Object-oriented languages define objects (types of things) that know how to perform methods (specific actions). Functional languages treat programming problems like mathematical relationships. Ruby is flexible, meaning that you can program in any of these styles however, it is primarily object oriented, with some strong functional influence. This book focuses slightly more on the functional aspects of Ruby than some other books.
標(biāo)簽： Object-oriented languages objects methods
上傳時間： 2016-08-05
上傳用戶：佳期如夢
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods。一本關(guān)于支持矢量機(jī)的英文入門書籍。
標(biāo)簽： Introduction Kernel-based Machines Learning
上傳時間： 2013-12-01
上傳用戶：hxy200501
cskmeans 聚類算法的一種 1. 分裂法(partitioning methods)：給定一個有N個元組或者紀(jì)錄的數(shù)據(jù)集，分裂法將構(gòu)造K個分組，每一個分組就代表一個聚類，K<N。而且這K個分組滿足下列條件：（1） 每一個分組至少包含一個數(shù)據(jù)紀(jì)錄；（2）每一個數(shù)據(jù)紀(jì)錄屬于且僅屬于一個分組（注意：這個要求在某些模糊聚類算法中可以放寬）；對于給定的K，算法首先給出一個初始的分組方法，以后通過反復(fù)迭代的方法改變分組，使得每一次改進(jìn)之后的分組方案都較前一次好，而所謂好的標(biāo)準(zhǔn)就是：同一分組中的記錄越近越好，而不同分組中的紀(jì)錄越遠(yuǎn)越好。使用這個基本思想的算法有：K-MEANS算法、K-MEDOIDS算法、CLARANS算法；
標(biāo)簽： partitioning cskmeans methods 聚類算法
上傳時間： 2014-01-16
上傳用戶：songyue1991
channel estimation for OFDM system,including the ls and mmse methods.User can compare the different.
標(biāo)簽： estimation different including the
上傳時間： 2016-08-22
上傳用戶：chenlong
Computationally efficient methods for blind decision feedback equalization of QAM signals
標(biāo)簽： Computationally equalization efficient decision
上傳時間： 2013-12-26
上傳用戶：wangyi39
Maximum Likelihood Methods in Radar Array Signal Processing
標(biāo)簽： Likelihood Processing Maximum Methods
上傳時間： 2013-12-29
上傳用戶：dave520l
Recent advances in experimental methods have resulted in the generation of enormous volumes of data across the life sciences. Hence clustering and classification techniques that were once predominantly the domain of ecologists are now being used more widely. This book provides an overview of these important data analysis methods, from long-established statistical methods to more recent machine learning techniques. It aims to provide a framework that will enable the reader to recognise the assumptions and constraints that are implicit in all such techniques. Important generic issues are discussed first and then the major families of algorithms are described. Throughout the focus is on explanation and understanding and readers are directed to other resources that provide additional mathematical rigour when it is required. Examples taken from across the whole of biology, including bioinformatics, are provided throughout the book to illustrate the key concepts and each technique’s potential.
標(biāo)簽： experimental generation advances enormous
上傳時間： 2016-10-23
上傳用戶：wkchong
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