Abstract: Many modern industrial, medical, and commercial applications require temperature measurements in the extended temperature rangewith accuracies of ±0.3°C or better, performed with reasonable cost and often with low power consumption. This article explains how platinumresistance temperature detectors (PRTDs) can perform measurements over wide temperature ranges of -200°C to +850°C, with absolute accuracyand repeatability better than ±0.3°C, when used with modern processors capable of resolving nonlinear mathematical equation quickly and costeffectively. This article is the second installment of a series on PRTDs. For the first installment, please read application note 4875, "High-Accuracy Temperature Measurements Call for Platinum Resistance Temperature Detectors (PRTDs) and Precision Delta-Sigma ADCs."
上傳時間： 2013-11-06
上傳用戶：WMC_geophy
自適應(Adaptive)神經網絡源程序 The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural Networks featuring different adaptation algorithms.~..~ There are 11 blocks that implement basically these 5 kinds of neural networks: 1) Adaptive Linear Network (ADALINE) 2) Multilayer Layer Perceptron with Extended Backpropagation algorithm (EBPA) 3) Radial Basis Functions (RBF) Networks 4) RBF Networks with Extended Minimal Resource Allocating algorithm (EMRAN) 5) RBF and Piecewise Linear Networks with Dynamic Cell Structure (DCS) algorithm A simulink example regarding the approximation of a scalar nonlinear function of 4 variables
標簽： collection implement Adaptive adaptive
上傳時間： 2015-04-09
上傳用戶：ywqaxiwang
Description: S-ISOMAP is a manifold learning algorithm, which is a supervised variant of ISOMAP. Reference: X. Geng, D.-C. Zhan, and Z.-H. Zhou. Supervised nonlinear dimensionality reduction for visualization and classification. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, 2005, vol.35, no.6, pp.1098-1107.
標簽： Description supervised algorithm S-ISOMAP
上傳時間： 2015-04-10
上傳用戶：wfeel
The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural Networks featuring different adaptation algorithms.~..~ There are 11 blocks that implement basically these 5 kinds of neural networks: 1) Adaptive Linear Network (ADALINE) 2) Multilayer Layer Perceptron with Extended Backpropagation algorithm (EBPA) 3) Radial Basis Functions (RBF) Networks 4) RBF Networks with Extended Minimal Resource Allocating algorithm (EMRAN) 5) RBF and Piecewise Linear Networks with Dynamic Cell Structure (DCS) algorithm A simulink example regarding the approximation of a scalar nonlinear function of 4 variables is included
標簽： Neural collection implement Adaptive
上傳時間： 2013-12-23
上傳用戶：teddysha
C-C方法及改進的C-C方法重構相空間的matlab程序 -------------------------------- 性能： 3000數據耗時3分鐘 -------------------------------- 參考文獻： 1、nonlinear dynamics, delay times, and embedding windows.pdf 2、基于改進的C-C方法的相空間重構參數選擇4.pdf -------------------------------- 文件夾說明： 1、C_C_Method_luzhenbo2.m - 程序主文件，直接運行此文件即可! 2、LorenzData.dll - 產生Lorenz離散數據 3、DuffingData.dll - 產生Duffing離散數據 4、RosslerData.dll - 產生Rossler離散數據 5、ccFunction.dll - 計算S(m,N,r,t) - 原C-C方法中計算S(m,N,r,t)，改進的C-C方法中計算S2(m,N,r,t) 6、ccFunction_luzhenbo.dll - 計算S(m,N,r,t) - 改進的C-C方法中計算S1(m,N,r,t) -------------------------------- 致謝： 此稿本次修改的部分靈感來源于與研學論壇網友“張文鴿”和“yangfanboy”的討論，在此表示感謝!
上傳時間： 2015-06-08
上傳用戶：lo25643
this demo is to show you how to implement a generic SIR (a.k.a. particle, bootstrap, Monte Carlo) filter to estimate the hidden states of a nonlinear, non-Gaussian state space model.
標簽： a.k.a. bootstrap implement particle
上傳時間： 2014-11-10
上傳用戶：caozhizhi
The cable compensation system is an experiment system that performs simulations of partial or microgravity environments on earth. It is a highly nonlinear and complex system.In this paper, a network based on the theory of the Fuzzy Cerebellum Model Articulation Controller(FCMAC) is proposed to control this cable compensation system. In FCMAC ,without appropriate learning rate, the control system based on FCMAC will become unstable or its convergence speed will become slow.In order to guarantee the convergence of tracking error, we present a new kind of optimization based on adaptive GA for selecting learning rate.Furthermore, this approach is evaluated and its performance is discussed.The simulation results shows that performance of the FCMAC based the proposed method is stable and more effective.
標簽： system compensation simulations experiment
上傳時間： 2015-08-26
上傳用戶：希醬大魔王
This folder contains all the codes based on Matlab Language for the book <《Iterative Methods for Linear and nonlinear Equations》, and there are totally 21 M files, which can solve most of linear and nonlinear equations problems.
標簽： Iterative the for Language
上傳時間： 2013-12-23
上傳用戶：cazjing
We address the problem of blind carrier frequency-offset (CFO) estimation in quadrature amplitude modulation, phase-shift keying, and pulse amplitude modulation communications systems.We study the performance of a standard CFO estimate, which consists of first raising the received signal to the Mth power, where M is an integer depending on the type and size of the symbol constellation, and then applying the nonlinear least squares (NLLS) estimation approach. At low signal-to noise ratio (SNR), the NLLS method fails to provide an accurate CFO estimate because of the presence of outliers. In this letter, we derive an approximate closed-form expression for the outlier probability. This enables us to predict the mean-square error (MSE) on CFO estimation for all SNR values. For a given SNR, the new results also give insight into the minimum number of samples required in the CFO estimation procedure, in order to ensure that the MSE on estimation is not significantly affected by the outliers.
標簽： frequency-offset estimation quadrature amplitude
上傳時間： 2014-01-22
上傳用戶：牛布牛
This paper examines the asymptotic (large sample) performance of a family of non-data aided feedforward (NDA FF) nonlinear least-squares (NLS) type carrier frequency estimators for burst-mode phase shift keying (PSK) modulations transmitted through AWGN and flat Ricean-fading channels. The asymptotic performance of these estimators is established in closed-form expression and compared with the modified Cram`er-Rao bound (MCRB). A best linear unbiased estimator (BLUE), which exhibits the lowest asymptotic variance within the family of NDA FF NLS-type estimators, is also proposed.
標簽： performance asymptotic examines non-data
上傳時間： 2015-12-30
上傳用戶：225588
