MATLAB神经网络43个案例分析.pdf与源码

切割方体的最优算法，用动态归划 Mathematica程序(The superior calculate way that incises a square body returns to row with the dynamic state)

这是一个关于建立分数布朗信号的Matlab程序。(Create Fractional Brownian Signal.)

我们在取样风格相适应的块为基础的压缩感知（BCS），以及投影驱动的Landweber迭代硬阈值化以重建视频，同时维纳滤波器（SPL）被用于在迭代过程，以减少噪音和块伪影。此外，从与运动估计和补偿在双方向所产生的残余结合重建被施加以改善重建品质。此外，加权矩阵采用变换域进一步优化。

用于计算随机序列线性复杂度的Berlekamp-Massey算法，已包装为matlab函数，省去复杂的算法调试过程(implement the inversionless Berlekamp-Massy algorithm in matlab)

悬架传递函数计算，包括输入时域信号和频域信号后对传递函数的计算(Suspension transfer function calculation, including the calculation of the transfer function after the input time-domain signal and frequency-domain signal)

matlab教程，方便的适用于初学者，中文版本(matlab tutorials, easy for beginners, the Chinese version)

人口灰色预测模型可以在数学建模中应用，预测人口数量的变化，灰常灰常灰常有用。(gm grey prediction may not be perfect but it s useful u know. used in mathmatical test for population prediction. very very useful)

interleaved buck pfc will help in reducing magnetics,sizes,ripple,and overall size of the board.will help a lot if the frequency is of the 100 khz

Compressive sampling is an emerging technique that promises to effectively recover a sparse signal from far fewer measurements than its dimension. The compressive sampling theory assures almost an exact recovery of a sparse signal if the signal is sensed randomly where the number of the measurements taken is proportional to the sparsity level and a log factor of the signal dimension. Encouraged by this emerging technique, this thesis briefly reviews the application of Compressive sampling in speech processing. It comprises the basic study of two necessary condition of compressive sensing theory: sparsity and incoherence. In this thesis, various sparsity domain and sensing matrix for speech signal and different pairs that satisfy incoherence condition has been compiled.

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