A Matlab toolbox for exact linear time-Invariant system identification is presented. The emphasis is on the variety of possible ways to implement the mappings from data to parameters of the data generating system. The considered system representations are input/state/output, difference equation, and left matrix fraction. KEYWORDS: subspace identification, deterministic subspace identification, balanced model reduction, approximate system identification, MPUM.
標(biāo)簽： identification time-Invariant presented emphasis
上傳時(shí)間： 2013-12-28
上傳用戶(hù)：wfl_yy
This paper addresses the issues relating to the enforcement of robust stability when implementing the Adaptive Inverse Control (AIC) scheme. In this scheme, an adaptive FIR filter is added to a closed-loop system in order to reduce the output error caused by external disturbances, enhancing the performance achieved by linear time-Invariant controllers alone.
標(biāo)簽： implementing enforcement addresses the
上傳時(shí)間： 2013-12-23
上傳用戶(hù)：佳期如夢(mèng)
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(biāo)簽： identification considered features separati
上傳時(shí)間： 2016-09-20
上傳用戶(hù)：FreeSky
Robust Pose Invariant Facial Feature Detection and Tracking in Real-Time
標(biāo)簽： Invariant Detection Real-Time Tracking
上傳時(shí)間： 2017-04-12
上傳用戶(hù)：gmh1314
從時(shí)域分析比較了ofdm和stbc與ofdm結(jié)合的性能差別-from time-domain analysis and comparison of OFDM stbc OFDM combined wi
上傳時(shí)間： 2013-06-05
上傳用戶(hù)：caozhizhi
HT47R20A-1時(shí)基(Time Base)使用介紹 HT47 系列單片機(jī)的時(shí)基可提供一個(gè)周期性超時(shí)時(shí)間周期以產(chǎn)生規(guī)則性的內(nèi)部中斷。時(shí)基的時(shí)鐘來(lái)源可由掩膜選擇設(shè)定為WDT 時(shí)鐘、RTC 時(shí)鐘或指令時(shí)鐘（系統(tǒng)時(shí)鐘/4）；其超時(shí)時(shí)間范圍可由掩膜選擇設(shè)定為“時(shí)鐘來(lái)源”/212~“時(shí)鐘來(lái)源”/215。如果時(shí)基發(fā)生超時(shí)現(xiàn)象，則其對(duì)應(yīng)的中斷請(qǐng)求標(biāo)志（TBF）會(huì)被置位，如果中斷允許，則產(chǎn)生一個(gè)中斷服務(wù)到08H 的地址。
上傳時(shí)間： 2013-11-15
上傳用戶(hù)：13925096126
Backpropagation Network Time-Series Forecasting 源碼, 經(jīng)典的BPN人工神經(jīng)網(wǎng)絡(luò)例子源碼
標(biāo)簽： Backpropagation Forecasting Time-Series Network
上傳時(shí)間： 2015-01-05
上傳用戶(hù)：tb_6877751
Unix和NT上NetWork Time網(wǎng)絡(luò)協(xié)議（4.0版本）
標(biāo)簽： NetWork Unix Time 4.0
上傳時(shí)間： 2014-01-01
上傳用戶(hù)：鳳臨西北
rtai-3.1-test3的源代碼(Real-Time Application Interface )
標(biāo)簽： Application Real-Time Interface rtai
上傳時(shí)間： 2014-11-22
上傳用戶(hù)：lps11188
S3C44BOX的BIOS。可使用的命令：help --- show help ? --- = help date --- show or set current date time --- show or set current time setweek --- set weekday clock --- show system running clock setmclk --- set system running clock setbaud ------ set baud rate ipcfg ------ show or set IP address load ------ load file to ram comload ------ load file from serial port run ------ run from sdram prog ------ program flash copy ------ copy flash from src to dst address boot ------ boot from flash backup ------ move bios to the top of flash md ------ show memory data move ------ move program from flash to sdram
標(biāo)簽： help date show current
上傳時(shí)間： 2015-01-22
上傳用戶(hù)：ANRAN
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