pr4

本程序由一对m序列优选对模二加生成一组平衡GOLD序列码，用于对直扩系统仿真之中，通过改变第二个m序列的初始状态可以生成不同的GOLD序列码(The program consists of a pair of m sequence optimization of mode two and generate a set of balanced GOLD sequence codes for DSSS system simulation, by changing the initial state of second m sequences can generate GOLD sequence code different)

After identifying the best MNT− 1 nodes with the simplified branch metric and the accumulated branch metric at stage NT − 1, we then calculate the LLR of each coded bit utilizing the standard squared Euclidian distance metric. The log-likelihood ratio (LLR) of a posteriori probability (APP) of each coded bit conditioned on the received signal y is normally calculated using the max-log approximation.

异步双馈风力发电机的模型，matlab搭建，可以参考(DFIG_skjhadal_dlsakdflak_slkflak;sl_)

Nonlinear Problem Files Collection (A collection of example programs and algorithms dealing with the solution of nonlinear problems. The following files are included (among others): damped Newton s method (see screenshot) Newton s method example, system case Fixpoint iteration. )

image rotation,for rotating skewed images of document images

先进PID控制及其MATLAB仿真 源程序(Advanced PID control and MATLAB simulation)

uniform quantization rgb matlab

----------------------------------------------------- This file produces the output file test_impulse.wav containing an approximation to the unit impulse (delta) function. The value of alpha on [0,1] determines the bandlimit of the approximation. This method is used to avoid the technical difficulties in producing (and reproducing) an ideal impulse (delta) function in audio. This file also produces the .wav audio file test_audio.wav which is an audio test vector intended to be used in the impulse response inversion experiment. (4/24/2002) NOTE: Impulse is bandlimited to alpha*Fmax where Fmax = Fs/2, or the Nyquist frequency.

matlab数据的预处理代码，rscore(preprocessor code matlab data, r score)

Edge detection result should be enhanced using linear method like Median filter to remove the garbage around the pupil to gain clear pupil to determine perfect centre. Get the centre of the pupil by counting the number of black pixels (zero value) of each column and row. Then get each row and column that has the maximum number of these black pixels. Then determine the center by simple calculation according to the image coordinate to set it correct on the image, consequently we can determine the radius of the pupil. Thus we can find the pupillary boundary (inner). A similar procedure is extended by using a coarse scale to locate the outer boundary (limbus) which can be apparent by using the mid-point algorithms of circle and ellipse.