allanvar_02

Character recognition of kannada system

target selection simmulation performance

Matlab code for the Simulation of the Maxwell-Dirac and Schrodinger-Poisson systems

说明：  对信号的功率谱估计采用BT法功率谱估计。在MATLAB中调试通过。(The power spectrum of the signal is estimated that the use of BT power spectrum estimation method. In MATLAB in the debugger through.)

说明：  压缩传感的几篇硕博士论文，可以帮助新手入门和毕业生写论文(Compressed sensing several Dissertations, and graduates can help beginners write papers)

Optical flow or optic flow is the pattern of apparent motion of objects, surfaces, and edges in a visual scene caused by the relative motion between an observer (an eye or a camera) and the scene.[2][3] The concept of optical flow was first studied in the 1940s and ultimately published by American psychologist James J. Gibson[4] as part of his theory of affordance. Optical flow techniques such as motion detection, object segmentation, time-to-collision and focus of expansion calculations, motion compensated encoding, and stereo disparity measurement utilize this motion of the objects surfaces and edges.[5][6]

In linear algebra, Gaussian elimination (also known as row reduction) is an algorithm for solving systems of linear equations. It is usually understood as a sequence of operations performed on the associated matrix of coefficients. This method can also be used to find the rank of a matrix, to calculate the determinant of a matrix, and to calculate the inverse of an invertible square matrix. The method is named after Carl Friedrich Gauss, although it was known to Chinese mathematicians as early as 179 AD (see History section).

该算法是根据自适应差分脉冲编码调制原理编写的算法，该算法利用了语音信号样点间的相关性，并针对语音信号的非平稳特点，使用了自适应预测(The algorithm is based on principles of adaptive differential pulse code modulation written algorithm, which samples the voice signal using the correlation between, and for non-stationary characteristics of speech signal using an adaptive prediction)

结合HCM和FCM优点的一种新的高效算法。(HCM and FCM combines the advantages of a new efficient algorithm.)

This is a case where a array is introduced with noise