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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."
標(biāo)簽：
PRTDs
ADC
高精度
溫度測(cè)量
上傳時(shí)間：
2013-11-06
上傳用戶：WMC_geophy
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自適應(yīng)(Adaptive)神經(jīng)網(wǎng)絡(luò)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(biāo)簽：
collection
implement
Adaptive
adaptive
上傳時(shí)間：
2015-04-09
上傳用戶：ywqaxiwang
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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(biāo)簽：
Description
supervised
algorithm
S-ISOMAP
上傳時(shí)間：
2015-04-10
上傳用戶：wfeel
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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(biāo)簽：
Neural
collection
implement
Adaptive
上傳時(shí)間：
2013-12-23
上傳用戶：teddysha
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C-C方法及改進(jìn)的C-C方法重構(gòu)相空間的matlab程序
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性能：
3000數(shù)據(jù)耗時(shí)3分鐘
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參考文獻(xiàn)：
1、Nonlinear dynamics, delay times, and embedding windows.pdf
2、基于改進(jìn)的C-C方法的相空間重構(gòu)參數(shù)選擇4.pdf
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文件夾說(shuō)明：
1、C_C_Method_luzhenbo2.m - 程序主文件，直接運(yùn)行此文件即可!
2、LorenzData.dll - 產(chǎn)生Lorenz離散數(shù)據(jù)
3、DuffingData.dll - 產(chǎn)生Duffing離散數(shù)據(jù)
4、RosslerData.dll - 產(chǎn)生Rossler離散數(shù)據(jù)
5、ccFunction.dll - 計(jì)算S(m,N,r,t) - 原C-C方法中計(jì)算S(m,N,r,t)，改進(jìn)的C-C方法中計(jì)算S2(m,N,r,t)
6、ccFunction_luzhenbo.dll - 計(jì)算S(m,N,r,t) - 改進(jìn)的C-C方法中計(jì)算S1(m,N,r,t)
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致謝：
此稿本次修改的部分靈感來(lái)源于與研學(xué)論壇網(wǎng)友“張文鴿”和“yangfanboy”的討論，在此表示感謝!
標(biāo)簽：
C-C
matlab
3000
程序
上傳時(shí)間：
2015-06-08
上傳用戶：lo25643
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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(biāo)簽：
a.k.a.
bootstrap
implement
particle
上傳時(shí)間：
2014-11-10
上傳用戶：caozhizhi
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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(biāo)簽：
system
compensation
simulations
experiment
上傳時(shí)間：
2015-08-26
上傳用戶：希醬大魔王
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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(biāo)簽：
Iterative
the
for
Language
上傳時(shí)間：
2013-12-23
上傳用戶：cazjing
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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(biāo)簽：
frequency-offset
estimation
quadrature
amplitude
上傳時(shí)間：
2014-01-22
上傳用戶：牛布牛
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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(biāo)簽：
performance
asymptotic
examines
non-data
上傳時(shí)間：
2015-12-30
上傳用戶：225588
