Matlab

ex5_1 I-型线性相位FIR滤波器 ex5_2 II-型线性相位FIR滤波器 ex5_3 III-型线性相位FIR滤波器 ex5_4 IV-型线性相位FIR滤波器 ex5_5 矩形窗频响 ex5_6 希尔伯特变换器设计－汉宁窗 ex5_7 低通滤波器设计－汉明窗 ex5_8 带通滤波器设计－布莱克曼窗 ex5_9 低通滤波器设计－凯塞窗 ex5_11 频率采样技术：低通，朴素法 ex5_12 频率采样技术：低通, 最优法T1 & T2 ex5_13 频率采样技术：带通, 最优法T1 & T2 ex5_14 频率采样技术：高通, 最优法T1 ex5_15 频率采样技术：差分器 ex5_16 频率采样技术： 希尔伯特变换器 ex5_17 利用Parks-McClella算法设计低通滤波器 ex5_18 用PM算法进行的带通滤波器设计 ex5_19 用PM算法进行的高通滤波器设计 ex5_20 用PM算法进行的阶梯滤波器设计 ex5_21 用PM算法进行的差分器设计 ex5_22 用PM算法进行的希尔伯特变换器设计(ex5_1 I-type linear phase FIR filter ex5_2 II-type linear phase FIR filter ex5_3 III-type linear phase FIR filter ex5_4 IV-type linear phase FIR filter rectangular window frequency response ex5_5 Hilbert ex5_6 converter design- Hanning window low-pass filter design ex5_7- Hamming window ex5_8 bandpass filter design- Blackman window ex5_9 low-pass filter design- Kaiser window ex5_11 sampling frequency: low-pass, a simple method ex5_12 sampling frequency: low-pass, optimal method T1 & T2 sampling frequency ex5_13: band-pass, optimal method T1 & T2 ex5_14 sampling frequency: high-pass, optimal method T1 sampling frequency ex5_15: differentiator sampling frequency ex5_16: Hilbert converter Parks-McClella use ex5_17 algorithm design low-pass filter PM algorithm ex5_18 with the band-pass filter design PM algorithm ex5_19 with the high-pass filter design PM algorithm used ex5_20 ladder filter design PM algorithm used ex5_21 differential design PM al)

3D Lattice Boltzmann (BGK) model of a fluid

IEEE 802.3 - 2012 Section Six IEEE Standard for Ethernet

matlab程序，关于BP神经网络的，修正函数，变学习速率(matlab program on BP neural network, correction function, variable learning rate)

Butter 函数的应用于低通滤波器，对应的仿真图形与代码(Butter function applied to low-pass filter corresponding to the simulation graphics and code)

基础教学,代码示例，适用于泛泛学习, 基本可以满足初学者的要求，很经典的例子(basic teaching for matlab,examples)

说明：  一个简单ARX画线, f f(a simple line drawing,)

关于RFID的LANDMARC算法与加权计算平均功率的计算(About RFID' s LANDMARC algorithm and the calculation of weighted average power)

解决最短路问题的MATLAB算法，只要输入邻接矩阵即可求出结果(MATLAB to solve the shortest path problem algorithm, the adjacency matrix can be obtained as long as the result of input)

PAGING IN COMPUTER MEMORY MANAGEMENT