demoApp

高频小信号放大器，采用1496模拟乘法器，分为调制解调模块(High-frequency small-signal amplifier, analog multiplier used 1496, divided into modem module)

说明：  用matlab程序模拟实现cdma系统的整个过程。包括并串、串并转换，m序列的产生，直接扩频、解扩，qpsk的调制解调，载波调制解调等。(Matlab simulation procedures used to achieve the whole process of cdma systems. Including and string SERDES, m sequence generation, direct spread spectrum, despreading, qpsk the modulation and demodulation, carrier modulation and demodulation, etc..)

texture analysis using ANN

book for clustering based method for edge detection in hyperspectral image.

数字滤波器设计程序，对各种滤波器设计，参数，原理进行了纤细说明(Digital filter design program, a variety of filter design parameters were slim that the principle)

将压缩感知用于谱估计中，根据论文谱压缩感知的一些程序(Compressive sensing (CS) is a new approach to simultaneous sensing and compression of sparse and compressible signals based on randomized dimensionality reduction. To recover a signal from its compressive measurements, standard CS algorithms seek the sparsest signal in some discrete basis or frame that agrees with the measurements. A great many applications feature smooth or modulated signals that are frequency sparse and can be modeled as a superposition of a small number of sinusoids. Unfortunately, such signals are only sparse in the discrete Fourier transform (DFT) domain when the sinusoid frequencies live precisely at the center of the DFT bins. When this is not the case, CS recovery performance degrades significantly. In this paper, we introduce a suite of spectral CS (SCS) recovery algorithms for arbitrary frequency sparse signals. The key ingredients are an over-sampled DFT frame, a signal model that inhibits closely spaced sinusoids, and classical sinusoid parameter e)

在3维里面重要的就是用MATLAB模拟空间多孔介质,得到实验基础(In 3-D inside the important thing is to use MATLAB simulation of porous media space, the basic experiment)

虽然奇异值分解（SVD）和特征值分解（EVD的）是行之有效的，可以通过先进的设施设备先进的算法，它不是通常所说，有一个内在的迹象，可以显着影响的不确定性的结论计算及诠释来自其结果。我们提供一个解决方案，标志模糊的问题确定了从奇异向量的内积和个人数据载体签署奇异向量的迹象。该数据可能有不同的载体，但它有它自身的定位和实际意义的选择方向，其中多数的向量点。这可以通过评估发现了内心的签署标志产品的总和。(Although the Singular Value Decomposition (SVD) and eigenvalue decomposition (EVD) are well-established and can be computed via state-of-the-art algorithms, it is not commonly mentioned that there is an intrinsic sign indeterminacy that can significantly impact the conclusions and interpretations drawn from their results. We provide a solution to the sign ambiguity problem by determining the sign of the singular vector from the sign of the inner product of the singular vector and the individual data vectors. The data vectors may have different orientation but it makes intuitive as well as practical sense to choose the direction in which the majority of the vectors point. This can be found by assessing the sign of the sum of the signed inner products. )

Ever got a movie subtitle file that won t match? Here is a code to correct time offset and speed of .idx, .srt and some other subtitle files. Drag-drop capable executable is also included.

说明：  例题全部代码. 薛定宇, 陈阳泉. 高等应用数学问题的Matlab求解.(All the code examples. Xue Dingyu, Chen Yangquan. MATLAB to solve higher applied mathematical problems.)