Adaptive Filter. This script shows the BER performance of several types of equalizers in a static channel with a null in the passband. The script constructs and implements a linear equalizer object and a decision feedback equalizer (DFE) object. It also initializes and invokes a maximum likelihood sequence estimation (MLSE) equalizer. The MLSE equalizer is first invoked with perfect channel knowledge, then with a straightforward but imperfect channel estimation technique.
The first task at hand is to set up the endpoints appropriately for this example. The following code switches the CPU clock speed
to 48 MHz (since at power-on default it is 12 MHz), and sets up EP2 as a Bulk OUT endpoint, 4x buffered of size 512, and EP6
as a Bulk IN endpoint, also 4x buffered of size 512. This set-up utilizes the maximum allotted 4-KB FIFO space. It also sets up
the FIFOs for manual mode, word-wide operation, and goes through a FIFO reset and arming sequence to ensure that they are
ready for data operations
//
// Histogram Sample
// This sample shows how to use the Sample Grabber filter for video image processing.
// Conceptual background:
// A histogram is just a frequency count of every pixel value in the image.
// There are various well-known mathematical operations that you can perform on an image
// using histograms, to enhance the image, etc.
// Histogram stretch (aka automatic gain control):
// Stretches the image histogram to fill the entire range of values. This is a "point operation,"
// meaning each pixel is scaled to a new value, without examining the neighboring pixels. The
// histogram stretch does not actually require you to calculate the full histogram. The scaling factor
// is calculated from the minimum and maximum values in the image.
北京大學ACM題
Here is a geometric problem. You have an angle and some squares in the first quadrant of the plane rectangular coordinates. The vertex of the angle is fixed on the origin O of the coordinates, and both of its radial lines are specified by the input. The sizes of the squares are also specified by the input, and the squares can shift vertically and horizontally. Now your job is to use the squares and the radial lines of the angle to enclose the maximum area, which excludes the area of the squares (see Figure 1). You should note that the edges of the squares must be parallel to the axes.
北京大學ACM比賽題目
Consider an infinite full binary search tree (see the figure below), the numbers in the nodes are 1, 2, 3, .... In a subtree whose root node is X, we can get the minimum number in this subtree by repeating going down the left node until the last level, and we can also find the maximum number by going down the right node. Now you are given some queries as "What are the minimum and maximum numbers in the subtree whose root node is X?" Please try to find answers for there queries.
Obtain the CDF plots of PAPR from an OFDM BPSK transmission specified per IEEE 802.11a specification
Per the IEEE 802.11a specifications, we 52 have used subcarriers. Given so, the theoretical maximum expected PAPR is 52 (around 17dB). However, thanks to the scrambler, all the subcarriers in an OFDM symbol being equally modulated is unlikely.
Using a small script, the cumulative distribution of PAPR from each OFDM symbol, modulated by a random BPSK signal is obtained
% EM algorithm for k multidimensional Gaussian mixture estimation
%
% Inputs:
% X(n,d) - input data, n=number of observations, d=dimension of variable
% k - maximum number of Gaussian components allowed
% ltol - percentage of the log likelihood difference between 2 iterations ([] for none)
% maxiter - maximum number of iteration allowed ([] for none)
% pflag - 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none)
% Init - structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none)
%
% Ouputs:
% W(1,k) - estimated weights of GM
% M(d,k) - estimated mean vectors of GM
% V(d,d,k) - estimated covariance matrices of GM
% L - log likelihood of estimates
%
pashload是應用在linux下的網絡帶寬測試源程序精確度比較高
/////////////////////////////////////
Pathload is a tool for estimating the available bandwidth
of an end-to-end path from a host S (sender) to a host R (receiver).
The available bandwidth is the maximum IP-layer
throughput that a flow can get in the path from S to R,
without reducing the rate of the rest of the traffic in the path.
用Fourier變換求取信號的功率譜---周期圖法
用Fourier變換求取信號的功率譜---分段周期圖法
用Fourier變換求取信號的功率譜---welch方法
功率譜估計----多窗口法(multitaper method ,MTM法)
功率譜估計----最大熵法(maxmum entmpy method,MEM法)
功率譜估計----多信號分類法(multiple signal classification,music法)Fourier transform to strike a signal to the power spectrum - the cycle of plans
Fourier transform to strike a signal to the power spectrum - Sub-cycle Method
Fourier transform to strike a signal to the power spectrum --- welch method
Power spectrum estimated more than window ---- Law (multitaper method, MTM)
---- Power spectrum estimate of maximum entropy (maxmum entmpy method, MEM)
---- More than the estimated power spectrum signal classification (multiple signal classification, music)