PSAT

河北工业大学的计算机组成小题的题库 绝对的题库 怎么来的就不说了 总之一句话 绝对的题库 而且题的总量不多(Hebei University of the theme of the computer in small absolute Exam exam how come not say a word question bank and question the absolute amount of not more than)

3GPP Spatial Channel Model Extended

We see that HTH matrix is almost diagonal as the off diagonal elements are nearly zero. So we are getting exact estimation in case of PRN INPUT due to diagonality of HTH matrix. As seen that the unknown inpulse response ( h ) and estimated impulse response ( hth ) are coming out to be exactly same. The estimation even gets better for large N .as we get the HTH matrix perfect diagonal. So we come to know that we can estimate the unknown parameters exactly when PRN input is used.

说明：  压缩感知的一个应用实例，对压缩后的信号用BP算法重构(An application of compressed sensing, on the compressed signal with the BP algorithm has)

Spectrum sensing using FFT Averaging Ratio (FAR) Algorithm

说明：  在matlab的条件下，开发BP网络的优化方法，对边坡的安全系数进行分析(In matlab under the conditions of the development of BP network optimization method, the slope factor of safety analysis)

Bi-dimensional Gabor filter with DC component compensation This version of the 2D Gabor filter is basically a bi-dimensional Gaussian function centered at origin (0,0) with variance S modulated by a complex sinusoid with polar frequency (F,W) and phase P described by the following equation: G(x,y,S,F,W,P)=k*Gaussian(x,y,S)*(Sinusoid(x,y,F,W,P)-DC(F,S,P)), where: Gaussian(x,y,S)=exp(-pi*S^2*(x^2+y^2)) Sinusoid(x,y,F,W,P)=exp(j*(2*pi*F*(x*cos(W)+y*sin(W))+P))) DC(F,S,P)=exp(-pi*(F/S)^2+j*P) File Id: 13776 Average rating: 0.0 Size: 1 KB # of reviews: 0 Submitted: 2007-01-26 Downloads: 274 Subscribers: 0 Keywords: gabor filter Stiven Schwanz Dias (Bi-dimensional Gabor filter with DC compo .. compensation This version of the 2D Gabor f ilter is basically a bi-dimensional Gaussian f unction centered at origin (0, 0) with variance S modulated by a complex sinuso id with polar frequency (F, W) and phase P described by the following equati on : G (x, y, S, F, W, P) = k* Gaussian (x, y, S)* (Sinusoid (x, y, F, W, P)- DC (F, S, P)), where : Gaussian (x, y, S) = exp (-pi* S* 2 ^ (x ^ 2 y ^ 2)) Sinusoid (x, y, F, W, P) = exp (j* (2* pi* F* (x* cos (W) y* sin (W)) P))) D C (F, S, P) = exp (-pi* (F/S) ^ 2* P j) File Id : 13776 Average rating : 0.0 Size :# 1 KB of reviews : 0 Submitted : 2007-01-26 Downloads : 274 Subscribers : 0 Keywords : gabor filter Stiven Schwanz Dias)

jacfar for reinforcement learning training

金属球体、椭球、视锥、圆盘、等腰三角形RCS MATLAB仿真实例(Simulation examples of metal sphere, ellipsoid, cone, disc and isosceles triangle RCS based on MATLAB)

目标跟踪，程序利用卡尔曼滤波器实现了对机动目标的跟踪。效果较好的运动模型。 (Target tracking, procedures realize the use of Kalman filter for maneuvering target tracking. Better model of the movement.)