orl_RBF_0822_1534

基于MATLAB的数字滤波器设计 MATLAB的基本知识 (Digital filter design based on MATLAB' s basic knowledge of MATLAB)

背包问题 贪心法C++实现 功能健康，绝对无毒(Greedy Knapsack Problem C++ Achieve functional health, is absolutely non-toxic)

鉴于载波相位观测量可提供高精度定位信息的特点,分析了在高动态环境获得载波相位观测量的三种可 能方法,对三种方法的估计精度和动态跟踪能力进行了比较. 提出了一种适合GPS 系统的高动态环境载波相位 测量方案.(View of the carrier phase measurements can provide accurate location information, analyzes the dynamic environment in the high carrier phase measurements to obtain three possible methods, three methods of estimation accuracy and dynamic tracking ability was compared. Presents a GPS system for high dynamic carrier phase measurement program.)

解决TSP问题以及VRP问题的标准算例，TSPLIB中整合了研究领域经常使用的44个算例，并且包含当前最优解(Standard solution of the TSP and VRP problem example, TSPLIB the integration of 44 frequently used examples of research areas, and contains the current optimal solution)

Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent unknown linear transform, namely the impulse response matrix operating on a sparse excitation, as in the linear model of speech production, for recovering compressive sensed speech. Since the linear transform is signal dependent and unknown, unlike the standard CS formulation, a codebook of transfer functions is proposed in a matching pursuit (MP) framework for CS recovery. It is found that MP is efficient and effective to recover CS encoded speech as well as jointly estimate the linear model. Moderate number of CS measurements and low order sparsity estimate will result in MP converge to the same linear transform as direct VQ of the LP vector derived the original signal. There is also high positive correlation between signal domain approximation and CS measurement domain approximation for a large variety of speech spectra.

《离散反问题》中的各类正则化matlab程序( Matlab package Regularization tools for the book 《discrete inverse problems》)

pap reduction in ofdm

清华张旭东老师《离散随机信号处理》教材第5章。本章首先简要复习经典谱估计的基本结论，然后分别讨论基于线性系统模型和复正弦模型的功率谱估计方法。(Qinghua Zhang Xudong teacher " discrete stochastic signal processing" textbook Chapter 5. This chapter begins with a brief review of the classical spectral estimation basic conclusion, and then discuss the power spectrum estimation based on linear system models and complex sinusoidal model approach.)

同步电机的原理的ppt 很详细的阐释了同步电机的原理图文并茂(Synchronous motor ppt principles explained in great detail the principles of synchronous motor with the aid of diagrams)

看到的一个有关图像锐化的MATLAB代码(See a MATLAB code for the image sharpening)