gabpdemo

Simulink_BFSK_RicianFading,simulink环境下RicianFading的BFSK误码率仿真(Simulink_BFSK_RicianFading, simulink environment RicianFading the BFSK bit error rate simulation)

ofdm code ber matlab snr

Run the ROI file by issuing the command ROI in the command window and a GUI screen will pop up, the screen may be used for selecting a Region of interest while viewing the full length movie and adjusting the region of interest accordingly, after hitting save the GUI will dismantle the movie to seperate images and will save them in current folder.The GUI panel is self explanatory and as such does not require any further explanations

it is a software ti localize wireless sensor network

产生一个含噪声矩形波，用小波分析和傅里叶变换分析进行信号噪声消除并比较两者的去噪声能力。(Produce a rectangular wave Noisy, wavelet analysis and Fourier transform analysis of signal-to-noise cancellation and compare the ability of both to noise.)

Simpson’s Rule Intgral

本代码用matlab编写Runge-Kutta算法程序，并且用ode45函数的编写代码进行对比分析。(The code is written using Runge-Kutta algorithm matlab program, and were analyzed by writing code ode45 function)

基于AR模型的Rayleigh瑞利衰落信道仿真源代码()

用matlab便的支持向量机预测方面的界面，希望对大家有用。(using Matlab would support vector machine interface projections, we hope that the right useful.)

Mammography is one of the available techniques for the early detection of masses or abnormalities which is related to breast cancer. Breast Cancer is the uncontrolled of cells in the breast region, which may affect the other parts of the body. The most common abnormalities that might indicate breast cancer are masses and calcifications. Masses appear in a mammogram as fine, granular clusters and also masses will not have sharp boundaries, so often difficult to identify in a raw mammogram. Digital Mammography is one of the best available technologies currently being used for the early detection of breast cancer. Computer Aided Detection System has to be developed for the detection of masses and calcifications in Digital Mammogram, which acts as a secondary tool for the radiologists for diagnosing the breast cancer. In this paper, we have proposed a secondary tool for the radiologists that help them in the segmentation and feature extraction process.