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gaussian-Pepper-Noise-Generator

  • 利用二元域的高斯消元法得到輸入矩陣H對應的生成矩陣G

    利用二元域的高斯消元法得到輸入矩陣H對應的生成矩陣G,同時返回與G滿足mod(G*P ,2)=0的矩陣P,其中P 表示P的轉置 使用方法:[P,G]=Gaussian(H,x),x=1 or 2,1表示G的左邊為單位陣

    標簽: 矩陣 二元 高斯 輸入

    上傳時間: 2014-11-27

    上傳用戶:semi1981

  • 這是一個非常簡單的遺傳算法源代碼

    這是一個非常簡單的遺傳算法源代碼,代碼保證盡可能少,實際上也不必查錯。對一特定的應用修正此代碼,用戶只需改變常數的定義并且定義“評價函數”即可。注意代碼 的設計是求最大值,其中的目標函數只能取正值;且函數值和個體的適應值之間沒有區別。該系統使用比率選擇、精華模型、單點雜交和均勻變異。如果用 Gaussian變異替換均勻變異,可能得到更好的效果。代碼沒有任何圖形,甚至也沒有屏幕輸出,主要是保證在平臺之間的高可移植性。讀者可以從ftp.uncc.edu, 目錄 coe/evol中的文件prog.c中獲得。要求輸入的文件應該命名為‘gadata.txt’;系統產生的輸出文件為‘galog.txt’。輸入的 文件由幾行組成:數目對應于變量數。且每一行提供次序——對應于變量的上下界。如第一行為第一個變量提供上下界,第二行為第二個變量提供上下界,等等。

    標簽: 算法 源代碼

    上傳時間: 2015-10-16

    上傳用戶:曹云鵬

  • 基于libsvm

    基于libsvm,開發的支持向量機圖形界面(初級水平)應用程序,并提供了關于C和sigma的新的參數選擇方法,使得SVM的使用更加簡單直觀.參考文章 Fast and Efficient Strategies for Model Selection of Gaussian Support Vector Machine 可google之。

    標簽: libsvm

    上傳時間: 2015-10-16

    上傳用戶:cuibaigao

  • A system simulation environment in Matlab/Simulink of RFID is constructed in this paper. Special at

    A system simulation environment in Matlab/Simulink of RFID is constructed in this paper. Special attention is emphasized on the analog/RF circuit.Negative effects are concerned in the system model,such as phase noise of the local oscillator,TX-RX coupling,reflection of the environment, AWGN noise,DC offset,I/Q mismatch,etc.Performance of the whole system can be evaluated by changing the coding method,parameters of building blocks,and operation distance.Finally,some simulation results are presented in this paper.

    標簽: environment constructed simulation Simulink

    上傳時間: 2014-01-09

    上傳用戶:zhangliming420

  • 本設計以凌陽16位單片機SPCE061A為核心控制器件

    本設計以凌陽16位單片機SPCE061A為核心控制器件,配合Xilinx Virtex-II FPGA及Xilinx公司提供的硬件DSP高級設計工具System Generator,制作完成本數字式外差頻譜分析儀。前端利用高性能A/D對被測信號進行采集,利用FPGA高速、并行的處理特點,在FPGA內部完成數字混頻,數字濾波等DSP算法。

    標簽: SPCE 061A 061 凌陽16

    上傳時間: 2014-11-23

    上傳用戶:bjgaofei

  • ITU-T G.729語音壓縮算法。 description: Fixed-point description of commendation G.729 with ANNEX B Coding

    ITU-T G.729語音壓縮算法。 description: Fixed-point description of commendation G.729 with ANNEX B Coding of Speech at 8 kbit/s using Conjugate-Structure Algebraic-Code-Excited Linear-Prediction (CS-ACELP) with Voice Activity Decision(VAD), Discontinuous Transmission(DTX), and Comfort Noise Generation(CNG).

    標簽: description commendation Fixed-point 729

    上傳時間: 2014-11-23

    上傳用戶:thesk123

  • This program includes: [5 7] convolutional code (encoder) + BPSK + AWGN + MAP (decoder). It evaluat

    This program includes: [5 7] convolutional code (encoder) + BPSK + AWGN + MAP (decoder). It evaluates Bit Error Rate and plots it versus SNR(signal to Noise Ratio).

    標簽: convolutional includes program encoder

    上傳時間: 2015-12-24

    上傳用戶:bruce5996

  • We address the problem of blind carrier frequency-offset (CFO) estimation in quadrature amplitude mo

    We address the problem of blind carrier frequency-offset (CFO) estimation in quadrature amplitude modulation, phase-shift keying, and pulse amplitude modulation communications systems.We study the performance of a standard CFO estimate, which consists of first raising the received signal to the Mth power, where M is an integer depending on the type and size of the symbol constellation, and then applying the nonlinear least squares (NLLS) estimation approach. At low signal-to noise ratio (SNR), the NLLS method fails to provide an accurate CFO estimate because of the presence of outliers. In this letter, we derive an approximate closed-form expression for the outlier probability. This enables us to predict the mean-square error (MSE) on CFO estimation for all SNR values. For a given SNR, the new results also give insight into the minimum number of samples required in the CFO estimation procedure, in order to ensure that the MSE on estimation is not significantly affected by the outliers.

    標簽: frequency-offset estimation quadrature amplitude

    上傳時間: 2014-01-22

    上傳用戶:牛布牛

  • In this article, we present an overview of methods for sequential simulation from posterior distribu

    In this article, we present an overview of methods for sequential simulation from posterior distributions. These methods are of particular interest in Bayesian filtering for discrete time dynamic models that are typically nonlinear and non-Gaussian. A general importance sampling framework is developed that unifies many of the methods which have been proposed over the last few decades in several different scientific disciplines. Novel extensions to the existing methods are also proposed.We showin particular how to incorporate local linearisation methods similar to those which have previously been employed in the deterministic filtering literature these lead to very effective importance distributions. Furthermore we describe a method which uses Rao-Blackwellisation in order to take advantage of the analytic structure present in some important classes of state-space models. In a final section we develop algorithms for prediction, smoothing and evaluation of the likelihood in dynamic models.

    標簽: sequential simulation posterior overview

    上傳時間: 2015-12-31

    上傳用戶:225588

  • An unsatisfactory property of particle filters is that they may become inefficient when the observa

    An unsatisfactory property of particle filters is that they may become inefficient when the observation noise is low. In this paper we consider a simple-to-implement particle filter, called ‘LIS-based particle filter’, whose aim is to overcome the above mentioned weakness. LIS-based particle filters sample the particles in a two-stage process that uses information of the most recent observation, too. Experiments with the standard bearings-only tracking problem indicate that the proposed new particle filter method is indeed a viable alternative to other methods.

    標簽: unsatisfactory inefficient property particle

    上傳時間: 2014-01-11

    上傳用戶:大三三

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