matlab-image-processing

Code source of Spectrum WVD

射频电路设计，微波设计中常常用到的smith原图，本程序利用MATLAB编程画出smith原图，可以帮助射频电路设计，比如画等功率匹配圆，等阻抗圆，等反射系数圆等。(RF circuit design, microwave design is often used smith artwork, this program using MATLAB to draw smith original programming that can help RF circuit design, such as painting and other power matching round, such as impedance circle, so the reflection coefficient circle and so on.)

该代码是用MATLAB写的。实现了JPEG压缩与解压缩的基本过程。适合图像方向的初学者学习使用。 MATLAB语言开发(The code is written in MATLAB. Achieve a JPEG compression and decompression of the basic process. Suitable for beginners to learn to use the image orientation. MATLAB language development)

A Robotics Object Oriented Package in C++

communication technology using Li-Fi method

这个程序可以实现对鼠标点击处的axes曲线做方框形的放大，可以利用 = ， ， < , > 调整放大倍数和放大的方框大小(This process can be achieved on the mouse to click the Office to do the box-shaped curve axes of amplification, can be used to adjust magnification' =' ,' ' ,' < ' ,' > ' and enlarge the size of the box)

Ear recognition in matlab

独立成份分析（ＩＣＡ）以及ｗｉｎｎｅｒ滤波 Source separation of complex signals with JADE. Jade performs `Source Separation in the following sense: X is an n x T data matrix assumed modelled as X = A S + N where o A is an unknown n x m matrix with full rank. o S is a m x T data matrix (source signals) with the properties a) for each t, the components of S(:,t) are statistically independent b) for each p, the S(p,:) is the realization of a zero-mean `source signal . c) At most one of these processes has a vanishing 4th-order cumulant. o N is a n x T matrix. It is a realization of a spatially white Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance sigma. This is probably better than no modeling at all...( Source separation of complex signals with JADE. Jade performs `Source Separation in the following sense: X is an n x T data matrix assumed modelled as X = A S+ N where o A is an unknown n x m matrix with full rank. o S is a m x T data matrix (source signals) with the properties a) for each t, the components of S(:,t) are statistically independent b) for each p, the S(p,:) is the realization of a zero-mean `source signal . c) At most one of these processes has a vanishing 4th-order cumulant. o N is a n x T matrix. It is a realization of a spatially white Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance sigma. This is probably better than no modeling at all...)

optical CHARACTER RECOGNITION with important diagrams.

说明：  ADMM是一个高效的优化算法，可以用在很多领域中，1范数是一种常用的目标函数。(ADMM is an effective, fast optimizing algorithm and can be used in many applications. 1-norm is a commonly used objective function.)