完整的isodata 迭代自组织的数据分析

this is a [ortion of machine drive designind code.

MATLAB编的一些计算算法，里面有详细的说明，仅供参考。(MATLAB compiled some of the calculation algorithm, which has detailed instructions for reference only.)

3-D FDTD code with PEC boundaries(3-D FDTD code with PEC boundaries. This MATLAB M-file implements the finite-difference time-domain solution of Maxwell s curl equations over a three-dimensional Cartesian space lattice comprised of uniform cubic grid cells. )

《matlab应用大全》赵海滨编著，清华大学出版社，第九章主讲二维数据可视化(The application of matlab Zhao Haibin compiled, tsinghua university press, chapter 9 on two-dimensional data visualization)

简要介绍gui界面操作的教程 适合初学者 里面包含部分实例 希望对各位有用(Brief tutorial gui interface operation for beginners which contains some examples you want to be useful)

[114.rar] Spectrum analyzer with USRP, GNU Radio and MATLAB (2009-09-14, matlab, 327KB, 68次) [USRP_Documentation.zip] usrp的全面介绍，接口介绍，工作原理，以及如何对它进行编程 (2010-12-17, Python, 720KB, 62次) [bbn_80211_trunk.zip] USRP（通用软件无线电）上实现的802.11：bbn80211，经测试在gnuradio3.1.1上通过（可以正常收发）(Universal Software Radio Peripheral (USRP) is a range of software-defined radios designed and sold by Ettus Research and its parent company, National Instruments. Developed by a team led by Matt Ettus, the USRP product family is intended to be a comparatively inexpensive hardware platform for software radio, and is commonly used by research labs, universities, and hobbyists.[1])

matlab code for DFE which id for ISI equaliser

TO FIND HISTOGRAM OF AN IMAGE

OFDM调制与解调，其中数字调制方式为QPSK。(OFDM modulation and demodulation, the digital modulation method is QPSK.)

Abstract—Demand Response (DR) and Time-of-Use (TOU) pricing refer to programs which offer incentives to customers who curtail their energy use during times of peak demand. In this paper, we propose an integrated solution to predict and re-engineer the electricity demand (e.g., peak load reduction and shift) in a locality at a given day/time. The system presented in this paper expands DR to residential loads by dynamically scheduling and controlling appliances in each dwelling unit. A decision-support system is developed to forecast electricity demand in the home and enable the user to save energy by recommending optimal run time schedules for appliances, given user constraints and TOU pricing the utility company. The schedule is communicated to the smart appliances over a self-organizing home energy network and d by the appliance control interfaces developed in this