text2voice

watermarking is the process of hiding information in the digital image.

说明：  汽车的轮胎垂向力计算模块，模型输入为汽车的实体参数、汽车的电动参数纵向和横向加速度，输出为汽车四个轮胎的垂向力。(Automobile tire vertical force calculation module, the model input for the entity parameters of the car, the electric parameters of the car' s longitudinal and lateral acceleration, the output of the vertical force of the car four tires.)

FASTICA算法，快速不动点，新的迭代公式,运行良好(FASTICA algorithm, fast fixed point, a new iterative formula, running well)

Creates wireless sensor network nodes in matlab.

基于机载的旋转式合成孔径雷达成像（包含点目标、多目标、时域脉压、频域脉压、RD算法）(Rotary Airborne Synthetic Aperture Radar imaging (including point target, multi-target, time domain pulse compression, frequency-domain pulse pressure, RD algorithm))

Microgrid paper based on PSO and MOPSO algorithm

基于matlab的DDS仿真程序 主要仿真了DDS的杂散特性(The DDS-based simulation program matlab simulation of the main characteristics of DDS spurious)

adaptive control of matlab simulink model

Standard analytic micromechanics analysis using the matlab programming language.

经典的香农采样定理认为,为了不失真地恢复模拟信号,采样频率应该不小于奈奎斯特频率(即模拟信号 频谱中的最高频率)的两倍.但是其中除了利用到信号是有限带宽的假设外,没利用任何的其它先验信息.采集到 的数据存在很大程度的冗余.Donoho等人提出的压缩感知方法(Compressed Sensing或Compressive Sampling, CS)充分运用了大部分信号在预知的一组基上可以稀疏表示这一先验信息,利用随机投影实现了在远低于奈奎斯 特频率的采样频率下对压缩数据的直接采集.该方法不仅为降低采样频率提供了一种新思路,也为其它科学领域 的研究提供了新的契机.该文综述性地阐述了压缩感知方法的基本原理,给出了其中的一些约束问题和估计方法, 并介绍压缩感知理论的相关问题———矩阵填充,最后讨论了其未来可能的应用前景. (According to the conventional Shannon s sampling theorem,in order to represent the analog signal,the sampling rate should not be less than twice the Nyquist sampling rate.Howev- er,this theorem only makes use of the bandwidth information.As a result,the collected data contain many redundant information.The recently proposed sampling method,compressed sens- ing or compressive sampling(CS),can collect compressed data at the sampling rate much lower than that needed in Shannon s sampling theorem by exploring the compressibility of the signal. This paper presents a review on the basic theory of CS.Some of the restrictions and recovery methods in CS are also discussed.Finally,some potential applications based on CS are presented. )