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一款工作于2.4 GHz 频段的带有源负载的高性能双平衡有源混频器0479-8023(2012)04-0538-07(A High Performance Double-Balanced Gilbert Mixer with Active Loads for 2.4-GHz ISM Band Application)

用局部参数最优化方法设计一个模型参考自适应系统,可调增益的初值Kc(0)=0.2，给定值r(t)为单位阶跃信号，即r(t)=A×1(t)。 要求： 1把连续系统离散化(采样时间可取0.1)。 2编制并运行这个系统的计算机程序(注意调整B值，使系统获得较好的自适应特性)。 3记录ym、yp的曲线 记录kp×kc的曲线 记录广义输出误差e的变化曲线。 4在参数收敛后，让Kp=2变为Kp=1，重新观察Kp×Kc及e的变化曲线。 5找出在确定的B值下，使系统不稳定的A值(阶跃信号的幅值)，并与用劳斯稳定判据计算的结果比较。 (With local parameter optimization method to design a model reference adaptive system, adjustable gain initial Kc (0) = 0.2, for a given value of r (t) for the unit step signal that r (t) = A × 1 ( t). Requirements: a continuous system discretization (sampling time of 0.1 preferred). 2 compiled and run the system computer program (Note B to adjust the value of the system to obtain better adaptive characteristics). 3 records ym, yp curve record kp × kc curve records generalized output error e curves. 4 parameter convergence, let Kp = 2 into the Kp = 1, re-observed Kp × Kc and e curves. B-5 to find value in determining the next, making the system unstable A value (step signal of amplitude), and using Routh stability criterion and the comparison of the results calculated.)

时频分析工具箱 内有魏格纳时频分布 Gabor 表示等(Time-Frequency Analysis Toolbox)

Hidden-Unit Conditional Random Fields 工具箱，可以用于训练linearCRF和和L.J.P. van der Maaten, M. Welling 提出的huCRF(We provide Matlab code that implements the training and evaluation of hidden-unit CRFs, as well as code to reproduce the results of our experiments. The code implements four different training algorithms: (1) a batch learner that uses L-BFGS, (2) a stochastic gradient descent learner, (3) an online perceptron training algorithm, and (4) an online large-margin perceptron algorithm. The code can also be used to perform (conditional) herding in hidden-unit CRFs. )

matlab学习资料，讲述了在matlab下如何计算阶乘。(matlab learning materials, about how to calculate the factorial in matlab.)

用于求解Saleh模型，实现对无记忆功放的求解(Saleh model for solving)

fuzzy logic is a good controller

文件中包含了杨大成《移动传播环境》中7.2.1.2小节的利用等面积法（MEA）实现经典功率谱的功率谱密度，自相关函数，自相关函数均方差。希望能帮助你们。(File contains POSTS " mobile communication environment" in section 7.2.1.2 the use of equal-area method (MEA) to achieve the classic power spectrum of the power spectral density, autocorrelation function, autocorrelation function of MSE. Hope you have help, I will continue to post updates more results.)

The model used for creating the reference voltage is shown in Fig. 4. First, photovoltaic output current (Ipv) and output voltage (Vpv) are passed through a first order low pass filter with a magnitude of G = 1 and a time constant of T = 0.01 seconds in order to filter out the high frequency components or harmonics from these signals as shown in Fig. 5 and Fig. 6. The filtered current and voltage signals (Ipv_F and Vpv_F) are then fed into the MPPT control block that uses the Incremental Conductance Tracking Algorithm. An algorithm that is based on the fact the slope of the PV array power curve shown in Fig. 7 is zero at the Maximum Power Point (MPP), positive on the left of the MPP, and negative on the right. The MPP can thus be tracked by comparing the instantaneous conductance (I/V) to the incremental conductance (∆ I/∆ V) [11] as in (1):

Integers is given a rectangular matrix. define: 1) The number of rows containing at least one zero element 2) the number of the column in which the longest series of the same elements