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Matlab 6_5 Matlab7_0 完全正式版Matlab 6_5 Matlab7_0 完全正式版..Matlab 6_5 Matlab7_0 完全正式版.(Matlab 6_5 Matlab7_0 fully fledged version of Matlab 6_5 Matlab ab7_0 fully fledged version of Matlab .. 6_5 Matlab7_0 fully fledged version.)

spectral residual augmented classical least square source code

BNB20 Finds the constrained minimum of a function of several possibly integer variables. ％ Usage: [errmsg,Z,X,t,c,fail] = ％ BNB20(fun,x0,xstatus,xlb,xub,A,B,Aeq,Beq,nonlcon,settings,options,P1,P2,...) ％ ％ BNB solves problems of the form: ％ Minimize F(x) subject to: xlb <= x0 <=xub ％ A*x <= B Aeq*x=Beq ％ C(x)<=0 Ceq(x)=0 ％ x(i) is continuous for xstatus(i)=0 ％ x(i) integer for xstatus(i)= 1 ％ x(i) fixed for xstatus(i)=2 ％(BNB20 Finds the constrained minimum of a fu nction of several possibly integer variables. % Usage : [errmsg, Z, X, t, c, fail] =% BNB20 (fun, x0, xstatus, xlb, xub, A, B, Aeq, Beq, nonlcon. settings, options, P1, P2, ...)%% BNB solves problems of the form : Minimize% F (x) subject to : xlb)

给定模拟信号和抽样频率，求出相应的序列和该信号的幅频特性(Given analog signal and the sampling frequency, to obtain the corresponding sequence and the signal amplitude-frequency characteristic)

HOUGH变换检测圆 MATLAB程序(HOUGH transform circle detection MATLAB program)

[Matlab source code]encryption algorithm

本书讲述了运用matlab处理图像，适合初学者，并包含源程序。(The book tells the story of the use of matlab image processing, suitable for beginners, and includes source.)

LocalbinaryPattern Code

“Fast Tracking via Dense Spatio-Temporal Context Learning,” In ECCV 2014的源代码，效果非常好。(In this paper, we present a simple yet fast and robust algorithm which exploits the spatio-temporal context for visual tracking. Our approach formulates the spatio-temporal relationships between the object of interest and its local context based on a Bayesian framework, which models the statistical correlation between the low-level features (i.e., image intensity and position) from the target and its surrounding regions. The tracking problem is posed by computing a confidence map, and obtaining the best target location by maximizing an object location likelihood function. The Fast Fourier Transform is adopted for fast learning and detection in this work. Implemented in MATLAB without code optimization, the proposed tracker runs at 350 frames per second on an i7 machine. Extensive experimental results show that the proposed algorithm performs favorably against state-of-the-art methods in terms of efficiency, accuracy and robustness.)

基于马尔可夫跳变的网络化控制系统倒立摆程序matlab仿真(Matlab simulation of inverted pendulum program of networked control system based on Markov jump)