16111990-C-interview-questions-and-answers

android font droid sans mono, developed by google.(remote desktop viewer for linux. efficient and usable.)

Activity Instrumentation Test Case for Andriod.

本书论述在MATLAB环境下如何实现神经网络，包括了常用的神经网络及相关理论，如BP神经 网络、RBF神经网络、SVM、SOM神经网络、灰色神经网络、决策树、随机森林、小波神经网络、NARX神经网络等以及各种优化算法与神经网络的结合。(This book discusses how to realize neural network in MATLAB environment, including the commonly used neural network and related theory, combined with the BP neural network, RBF neural network, SVM, SOM neural network, grey neural network, decision tree, random forest, wavelet neural network and NARX neural network, optimization algorithm and neural network.)

关于Python的一些资料，帮助快速学习Python(The Guide of Python Quickly)

说明：  isight应用实例，帮助初学者快速掌握isight使用方法(ISIGHT application examples help beginners quickly master the use of iSIGHT)

说明：  稳健自适应波束形成，Wiley出版社，是一本有关MVDR波束形成稳健性分析的好书。(The latest research and developments in robust adaptive beamforming Recent work has made great strides toward devising robust adaptive beamformers that vastly improve signal strength against background noise and directional interference. This dynamic technology has diverse applications, including radar, sonar, acoustics, astronomy, seismology, communications, and medical imaging. There are also exciting emerging applications such as smart antennas for wireless communications, handheld ultrasound imaging systems, and directional hearing aids. Robust Adaptive Beamforming compiles the theories and work of leading researchers investigating various approaches in one comprehensive volume. Unlike previous efforts, these pioneering studies are based on theories that use an uncertainty set of the array steering vector. The researchers define their theories, explain their methodologies, and present their conclusions. Methods presented include: Coupling the standard Capon beamformers with a spher)

computational fluid dynamics

this is a plc program

说明：  参考文献方面的资料，帮助其他人更好的怎样使用参考文献(Reference information, help others better how to use the reference)

高斯烟羽模型2D的Python实现。用于污染物/危险物品扩散分析。(Gauss plume model 2D Python implementation. For the analysis of pollutant diffusion/dangerous goods.)