时频分析工具箱

matlab receiver for image transmission using usrp

对网格进行平滑，利用汉宁窗对海底地形进行平滑。直接输入函数即可。(Smoothing of the grid, the use of Hanning smoothing of the submarine topography. Can be directly input function.)

Business Cycle Uncertainty and Economic Welfare

wavlet based texture synthesis.

压缩感知雷达信号处理相关文献，包括英文最初的基础文章以及很好的综述性文章，对学习信号处理压感方向的同学会有所帮助！(Compressed sensing radar signal processing literature, including English first base articles, and good review article, to learn the direction of the signal processing pressure sensitive students will be helpful!)

Generador de señ ales Seno y Coseno

Buck电路的Simulink电路仿真,可以运行验证Buck电路的工作原理。(Buck circuit, circuit simulation, Simulink can run to verify the working principle of the Buck circuit.)

数字宽带接收机的信道化处理下的常规雷达信号的信号检测与脉内调制模式识别(The digital wideband receiver channel of the conventional radar signal under the condition of signal detection and intra-pulse modulation pattern recognition)

基于人工势场的岔路口的道路建模研究（程序）(Based on Artificial Potential Field Modeling road fork)

本书是The IMA Volumes in Mathematics and its Applications系列的一本，由Springer-Verlag发表，用于交流每年数学规划算法方面的新成果，希望对于广泛的科学团体有帮助。 许多工程，运筹，和科学应用包括离散或连续的决策变量，以及这些决策变量的非线性关系。这种 Mixed-integer nonlinear programming （MINLP，混合整数非线性规划），兼具来自非线性问题的非凸函数优化，以及来自整数的离散优化，这两方面的挑战。这种问题是优化问题里面建模最灵活的类型之一，但是因为它范围极广，在最一般的情况下，它是几乎无法解的。然而，日渐壮大的研究者和程序员队伍，包括化学工程，运筹研究者，工业工程师，机械工程师，经济学家，统计学家，计算机科学家，运营经理，和数学程序员，都对求解大规模MINLP问题产生兴趣。(Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization but because its scope is so broad, in the most general cases it is hopelessly intractable. Nonetheless, an expanding body of researchers and practitioners ― including chemical engineers, operations researchers, industrial engineers, mechanical engineers, economists, statisticians, computer scientists, operations managers, and mathematical programmers ― are interested in solving large-scale MINLP instances.)