Classify using the minimum error criterion via histogram estimation of the densities
標簽： estimation the criterion densities
上傳時間： 2015-08-28
上傳用戶：wang0123456789
The equal-area theorem●This is sinusoidal PWM (SPWM)●The equal-area theorem can be appliedto realize any shape of waveforms ●Natural sampling●Calculation based on equal-area criterion●Selected harmonic elimination●Regular sampling●Hysteresis-band control●Triangular wave comparison withfeedback control
上傳時間： 2013-11-22
上傳用戶：linyao
基于LabVIEW和單片機的空調溫度場測量系統的研究:室內溫度是空調系統舒適性的重要指標,對其及時、準確地測量顯得非常重要。介紹單片機AT89C51 和數字式、單總線型溫度傳感器DS18B20 組成矩形測量網絡采集空調室內40 點溫度,LabVIEW作為開發平臺,二者之間通過串口實現數據通信,利用LabVIEW強大的數據處理和顯示功能對采集的空調溫度場數據進行實時處理、分析和顯示,詳細介紹了系統的硬件結構和軟件模塊的設計方案。關鍵詞:單片機;DS18B20 ;LabVIEW;串行通信 Abstract : Temperature is a very important criterion of air condition system′s comfort , so it is very significant to measure it accurately and real timely. This paper int roduces a data acquisition system of measuring 40 point s temperature for air condition room based on single wire digital sensor DS18B20 and microcont roller AT89C51 which are composed of rectangle measuring meshwork. The data communication between LabVIEW and microcont roller is executed via serial port ,and the temperature field data of air condition room are processed analyzed and displayed on LabVIEW. The hardware and software modules are also given in detail.Keywords : single chip ;DS18B20 ;LabVIEW; serial communication
上傳時間： 2014-05-05
上傳用戶：KSLYZ
The Molgedey and Schuster decorrelation algorithm, having square mixing matrix and no noise . Truncation is used for the time shifted matrix, and it is forced to be symmetric . The delay Tau is estimated . The number of independent components are calculated using Bayes Information criterion (BIC), with PCA for dimension reduction.
標簽： decorrelation and algorithm Molgedey
上傳時間： 2013-12-13
上傳用戶：c12228
The problem of ¯ nding a linear discriminant function will be formulated as a problem of minimizing a criterion function
標簽： problem discriminant formulated function
上傳時間： 2014-11-30
上傳用戶：15071087253
he algorithm is equivalent to Infomax by Bell and Sejnowski 1995 [1] using a maximum likelihood formulation. No noise is assumed and the number of observations must equal the number of sources. The BFGS method [2] is used for optimization. The number of independent components are calculated using Bayes Information criterion [3] (BIC), with PCA for dimension reduction.
標簽： equivalent likelihood algorithm Sejnowski
上傳時間： 2016-09-17
上傳用戶：Altman
The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order
標簽： identification considered features separati
上傳時間： 2016-09-20
上傳用戶：FreeSky
The toolbox solves a variety of approximate modeling problems for linear static models. The model can be parameterized in kernel, image, or input/output form and the approximation criterion, called misfit, is a weighted norm between the given data and data that is consistent with the model. There are three main classes of functions in the toolbox: transformation functions, misfit computation functions, and approximation functions. The approximation functions derive an approximate model from data, the misfit computation functions are used for validation and comparison of models, and the transformation functions are used for deriving one model representation from another. KEYWORDS: Total least squares, generalized total least squares, software implementation.
標簽： approximate The modeling problems
上傳時間： 2013-12-20
上傳用戶：15071087253
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).
標簽： from eliminates PRINCIPLE algorithm
上傳時間： 2016-11-27
上傳用戶：凌云御清風
function [U,V,num_it]=fcm(U0,X) ％ MATLAB (Version 4.1) Source Code (Routine fcm was written by Richard J. ％ Hathaway on June 21, 1994.) The fuzzification constant ％ m = 2, and the stopping criterion for successive partitions is epsilon =??????. ％*******Modified 9/15/04 to have epsilon = 0.00001 and fix univariate bug******** ％ Purpose:The function fcm attempts to find a useful clustering of the ％ objects represented by the object data in X using the initial partition in U0.
標簽： fcm function Version Routine
上傳時間： 2014-11-30
上傳用戶：二驅蚊器
