lpcc-speech-recognition-master

economic load dispatchnasnlasndl

IIR数字滤波器的设计 上学的时候一直不知道如何用C语言来编写IIR滤波器，终于找到了，上传给大家 希望能帮到大家。(IIR digital filter design when the school did not know how to use C language to write IIR filters, and finally found it, upload to hope to help you.)

【matlab编程代做】8QAM通过AWGNchannel后的误码率([Matlab] 8QAM by doing some programming error rate after AWGNchannel)

IEEE 14 bus data

说明：  现代海战需要功能综合的作战平台和性能优良的 武器系统来应对，海战场复杂多维的环境因素对海上 兵力运用有很大的影响。因此，如何准确建立海战场 的评估指标体系并进行科学评判是指挥员做出决策的 重要前提。目前，海战场环境评估的方法有层次分析 法、模糊评判法、指数法等11’21。针对这些方法主观性 比较强等不足，本文引入云重心的评估方法简单易行， 科学有效，可操作性强。 基于云重心方法的海战场环境评估(Modern naval warfare needs integrated operational platforms and excellent weapon systems to cope with. The complex and multi-dimensional environmental factors of naval battlefield have a great impact on the use of naval forces. Therefore, how to accurately establish the evaluation index system of sea battlefield and make scientific evaluation is an important prerequisite for commanders to make decisions. At present, the methods of Marine Battlefield Environment Assessment include analytic hierarchy process, fuzzy evaluation, index method and so on. In view of these shortcomings, such as strong subjectivity, this paper introduces cloud gravity center evaluation method which is simple, scientific and effective, and operable. Sea Battlefield Environment Assessment Based on Cloud Barycenter Method)

this program simulate a turbo equalizer for known and unknown channel for 16 qam

基于matlab的倒车模糊控制器设计，避免 死区 问题(Matlab fuzzy controller based on the reverse design, to avoid the ‘dead zone’ problem)

计算BPSK在AWGN下得误码率。其中，设置高斯白噪声的功率为1，也即是归一化功率(calculate the BER of BPSK under AWGN channel)

matlab使用文本文件进行数据存取详细过程说明(matlab using a text file for data access detailed process description)

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.