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金属偏最小二乘回归建模程序，附带详细说明。(Metal partial least squares regression modeling procedures, with detailed instructions.)

可以实现大规模的bfgs功能，进行目标函数的最优化求解，即L-BFGS(Can achieve large scale bfgs function, the objective function is the most optimal solution, ie, L-BFGS)

four quadrant induction motor

Algorithm to find the melody of a polyphonic music signals.

一连续平稳的随机信号x(t)，自相关函数RX(t)=e-/t/，信号x(t)为加性噪声所干扰，噪声是白噪声，测量值的离散值Z(k)为已知，TS=0.02s。 -3.2，-0.8，-14，-16，-17，-18，-3.3，-2.4， -18，-0.3，-0.4，-0.8，-19，-2.0，-1.2，-11，-14，-0.9，0.8，10，0.2，0.5，-0.5，2.4，-0.5，0.5，-13，0.5，10，-12，0.5，-0.6，-15，-0.7，15，0.5，-0.7，-2.0，-19，-17，-11，-14。 自编卡尔曼滤波递推程序，估计信号x(t)的波形。(A continuous stationary random signal x (t), the autocorrelation function RX (t) = e-/ t /, the signal x (t) is additive noise of the interference, noise is white noise, the measured value of the discrete values ​ ​ Z (k ) are known, TS = 0.02s. -3.2,-0.8,-14,-16,-17,-18,-3.3,-2.4,-18,-0.3,-0.4,-0.8,-19,-2.0,-1.2,-11,-14 ,-0.9,0.8,10,0.2,0.5,-0.5,2.4,-0.5,0.5,-13,0.5,10,-12,0.5,-0.6,-15,-0.7,15,0.5,-0.7,-2.0,-19,-17,-11,-14. Self Kalman filter recursive procedure, the estimated signal x (t) waveform.)

一种新的稀疏问题的直接求解算法——平滑l0算法(Sparse problems can by directly solved by a novel algorithm-- smoothed l0 method)

说明：  cegui使用说明,初学者可以看看,对api的介绍(cegui cegui cegui )

设计了一种具有异周期毗邻结构的新型循环前缀,提出了相应的OFDM 频偏估计算法。该异周期毗邻结 构循环前缀由CP1 和CP2 两部分构成,使OFDM 符号具有双周期特征。通过引入较短的CP1 ,牺牲极少的资源, 可以有效克服现有频偏估计方法中的固定频偏估计范围的缺陷,同时具有频偏估计范围大,精度高的特点。(This paper proposes a heter2cycle abutted CP st ructure and a two2step OFDM carrier f requency calibration algorithm. The cyclic prefix of the new cyclic prefix is made up of CP1 and CP2 , which provide the character of double2cycle for OFDM symbol. By int roducing a short CP1 , the proposed algorithm can overcome the defect of fixed f requency off set estimation range in current f requency estimation method , and achieves larger f requency esti2 mation range while obtaining fine f requency calibration.)

VAR or VARX code for Matlab

求时间序列的功率谱，包括周期图法和自相关函数法(Find the power spectrum of the time series, including periodogram and autocorrelation function method)