無線通信的各種運動模型。適用于移動通信、無線傳感器網絡等領域。 包括：Random walk、random waypoint、random direction、boundless simulation area、 gauss-markov等運動模型 - probabilistic random walk
標簽： random simulation direction boundless
上傳時間： 2014-11-12
上傳用戶：libinxny
This m file simulates a differential phase shift keyed (DPSK) ultra wide bandwidth(UWB) system using a fifth derivative waveform equation of a Gaussian pulse.
標簽： differential bandwidth simulates system
上傳時間： 2014-01-03
上傳用戶：784533221
完全的二維數值積分程序 給出自變量和函數值的矩陣，便可以計算其二重積分。這里采用simpson積分法 比matlab自帶的dblquad好用多了，霍霍！ 同時附有口徑場用Gaussian-Lagurrer函數展開程序
上傳時間： 2014-01-08
上傳用戶：xc216
In this project we analyze and design the minimum mean-square error (MMSE) multiuser receiver for uniformly quantized synchronous code division multiple access (CDMA) signals in additive white Gaussian noise (AWGN) channels.This project is mainly based on the representation of uniform quantizer by gain plus additive noise model. Based on this model, we derive the weight vector and the output signal-to-interference ratio (SIR) of the MMSE receiver. The effects of quantization on the MMSE receiver performance is characterized in a single parameter named 鈥漞quivalent noise variance鈥? The optimal quantizer stepsize which maximizes the MMSE receiver output SNR is also determined.
標簽： mean-square multiuser receiver project
上傳時間： 2014-11-21
上傳用戶：ywqaxiwang
Generate Possion Dis. step1:Generate a random number between [0,1] step2:Let u=F(x)=1-[(1/e)x] step3:Slove x=1/F(u) step4:Repeat Step1~Step3 by using different u,you can get x1,x2,x3,...,xn step5:If the first packet was generated at time [0], than the second packet will be generated at time [0+x1],The third packet will be generated at time [0+x1+x2], and so on …. Random-number generation 1.static method random from class Math -Returns doubles in the range 0.0 <= x < 1.0 2.class Random from package java.util -Can produce pseudorandom boolean, byte, float, double, int, long and Gaussian values -Is seeded with the current time of day to generate different sequences of numbers each time the program executes
標簽： Generate Possion between random
上傳時間： 2017-05-25
上傳用戶：bibirnovis
碩士論文，基于強背景噪聲下的語言端點檢測算法及實現。本文總結了現有的典型語音端點檢測算法，深入分析了各算法的基本原理，比較 其優缺點，并給出了仿真結果。在此基礎上，分析了現有語音信號的結構特點和特征參 數，提出了在較強背景噪聲環境下的兩種語音端點檢測新算法。分別是基于多子帶墑的 語音端點檢測算法和基于Gaussian一右~a模型的語音端點檢測算法。并給出了仿真 結果。從仿真結果可以看出在常見的噪聲環境下，算法魯棒性較好，在較低的信噪比下 仍能比較準確地檢測到語音信號的端點。
上傳時間： 2017-07-17
上傳用戶：asasasas
介紹回歸問題中高斯過程的應用，C. E. Rasmussen & C. K. I. Williams, Gaussian Processes for Machine Learning,
上傳時間： 2017-07-25
上傳用戶：skfreeman
The Kalman filter is an efficient recursive filter that estimates the state of a linear dynamic system from a series of noisy measurements. It is used in a wide range of engineering applications from radar to computer vision, and is an important topic in control theory and control systems engineering. Together with the linear-quadratic regulator (LQR), the Kalman filter solves the linear-quadratic-Gaussian control problem (LQG). The Kalman filter, the linear-quadratic regulator and the linear-quadratic-Gaussian controller are solutions to what probably are the most fundamental problems in control theory.
標簽： filter efficient estimates recursive
上傳時間： 2017-08-06
上傳用戶：風之驕子
Consider a BPSK and a QPSK system for the following two cases: 1) The probability that the symbol 1 is sent and the probability that the symbol 0 is sent are all the same. 2) The probability that the symbol 1 is sent is two times than the probability that the symbol 0 is sent. Assume that the noise is Gaussian distributed with mean=0 and 2 = 1.
標簽： probability following the Consider
上傳時間： 2017-08-15
上傳用戶：凌云御清風
SiftGPU is an implementation of SIFT [1] for GPU. SiftGPU processes pixels parallely to build Gaussian pyramids and detect DoG Keypoints. Based on GPU list generation, SiftGPU then uses a GPU/CPU mixed method to efficiently build compact keypoint lists. Finally keypoints are processed parallely to get their orientations and descriptors.
標簽： SiftGPU implementation processes parallely
上傳時間： 2013-11-27
上傳用戶：zhangjinzj
