chp2ex1gui

Edge detection result should be enhanced using linear method like Median filter to remove the garbage around the pupil to gain clear pupil to determine perfect centre. Get the centre of the pupil by counting the number of black pixels (zero value) of each column and row. Then get each row and column that has the maximum number of these black pixels. Then determine the center by simple calculation according to the image coordinate to set it correct on the image, consequently we can determine the radius of the pupil. Thus we can find the pupillary boundary (inner). A similar procedure is extended by using a coarse scale to locate the outer boundary (limbus) which can be apparent by using the mid-point algorithms of circle and ellipse.

用于初学者学习径向基函数神经网络，可以了解径向基函数神经网络的预测程序。对径向基函数神经网络有一个大体的了解。(For beginners to learn the radial basis function neural network prediction program can understand radial basis function neural network. Radial basis function neural network has a general understanding.)

适合初级学习MatLab的用户使用,讲解的比较清晰,很适合于学习(suitable for the initial study MatLab users, on the clear, well suited to learning)

说明：  给出了一个控制系统的模型，此模型采用ＭＡＴＬＡＢ模块搭建，解决跟踪问题(Gives a control system model, this model structures using MATLAB module to address the tracking problem)

SERIAL ACQUISITION OF PSEUDO NOISE PN

The model used for creating the reference voltage is shown in Fig. 4. First, photovoltaic output current (Ipv) and output voltage (Vpv) are passed through a first order low pass filter with a magnitude of G = 1 and a time constant of T = 0.01 seconds in order to filter out the high frequency components or harmonics from these signals as shown in Fig. 5 and Fig. 6. The filtered current and voltage signals (Ipv_F and Vpv_F) are then fed into the MPPT control block that uses the Incremental Conductance Tracking Algorithm. An algorithm that is based on the fact the slope of the PV array power curve shown in Fig. 7 is zero at the Maximum Power Point (MPP), positive on the left of the MPP, and negative on the right. The MPP can thus be tracked by comparing the instantaneous conductance (I/V) to the incremental conductance (∆ I/∆ V) [11] as in (1):

matlab下实现模拟退火算法的程序，非常好非常实用的程序！(matlab simulated annealing algorithm under the procedures, a very good program very useful!)

Parzen windows needed for Gaussian mixture to evaluate the pdf

高版本matlab的NC插件，7.0以后版本使用。无需安装。(High version of Matlab NC plug, 7.0 or later. Requires no installation.)

MATLAB neural network 30 case studies _MATLAB Chinese Forum _2010_P286.pdf