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
simulates coin tossing. Let the program toss a coin each time the user chooses the “Toss Coin” menu option. Count the number of times each side of the coin appears. Display the results. The program should call a separate method flip that takes no arguments and returns false for tails and true for heads. [ Note: If the program realistically simulates coin tossing, each side of the coin should appear approximately half the time.]
This program uses the HF flag of a FIFO to trigger reads, guaranteeing that the FIFO is never blocked for the writer, giving high throughput for the reader (bursts of D/2 = 128) and guaranteeing that the the reader will not be stuck in the top half of the FIFO.
％ 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
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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)
* acousticfeatures.m: Matlab script to generate training and testing files from event timeseries.
* afm_mlpatterngen.m: Matlab script to extract feature information from acoustic event timeseries.
* extractevents.m: Matlab script to extract event timeseries using the complete run timeseries and the ground truth/label information.
* extractfeatures.m: Matlab script to extract feature information from all acoustic and seismic event timeseries for a given run and set of nodes.
* sfm_mlpatterngen.m: Matlab script to extract feature information from esmic event timeseries.
* ml_train1.m: Matlab script implementation of the Maximum Likelihood Training Module.
?ml_test1.m: Matlab script implementation of the Maximum Likelihood Testing Module.
?knn.m: Matlab script implementation of the k-Nearest Neighbor Classifier Module.
實現8比特字節的RS糾錯編碼，可以指定極性校驗字節數目，能產生的最大校驗序列長度為255字節（含極性校驗字節）.This is an implementation of a Reed-Solomon code with 8 bit bytes, and a configurable number of parity bytes. The maximum sequence length (codeword) that can be generated is 255 bytes, including parity bytes.
包括使用修正Gram-Schmit算法實現QR分解，自編LU分解、利用冪法和反冪法計算矩陣最大和最小特征值的程序。例外附有使用這些算法的例子供參考。 QR decomposition algorithm based on modified Gram-Schmit LU decomposition algorithm algorithm used to find maximum and minimum eigenvalue based on power and inverse power method and some examples are also included.
