bios-256k

4—20mA电流变送器设计电路，说明的非常详细。保你一看就会。(4-20mA current transmitter circuit design, described in great detail. Will ensure you a look.)

说明：  CC2592 hex fie for 6lowpan

波形仿真，可帮助初学者了解超声波形形成原理(Waveform simulation to help beginners understand the principle of ultrasonic shape formation)

Java J2me坦克游戏源码，界面和游戏机中的有些区别，可发四种炸弹，也挺有意思的，包括完整的java代码文件。

说明：  提出一种基于桶排序的双层模型预测控制方法。对电容 电压进行桶排序，将电压排序后的子模块按次序等分为若干组，通过第一层模型预测控制确定需要插入桥臂的 组数，再通过第二层模型预测控制进一步确定需要插入的子模块。在 PSCAD/EMTDC 下搭建模块化多电平换 流器仿真系统，验证了所提方法的有效性。(A two-level model predictive control method based on bucket sorting is proposed. The capacitor voltage is sorted in buckets. The sub modules are divided into several groups in order. The number of groups that need to be inserted into the bridge arm is determined by the first level model predictive control, and the sub modules that need to be inserted are further determined by the second level model predictive control. In PSCAD / EMTDC, a modular multilevel converter simulation system is built to verify the effectiveness of the proposed method.)

用于社区发现领域实验研究，四大真实网络football club，dolphins，karate，polbooks(community detection dataset)

资源描述本程序介绍wpf中3d的有关测试，并且附加wpf中3D的动画功能，在程序里，3D模型能够做无规则运动，并且还附加了，按照自定义路径运行的过程，对此有兴趣的方便学习。

对储能模拟惯性进行了整理分析，可用于逆变器VSG控制(The storage simulation inertia is analyzed and analyzed, which can be used for inverter VSG control.)

统计学习是计算机及其应用领域的一门重要的学科本书全面系统地介绍了统计学习的主要方法，特别是监督学习方法，包括感知机、K近邻法、朴素贝叶斯法、决策树、逻辑斯谛回归、与最大熵模型、支持向量机、提升方法、EM算法、隐马尔可夫模型和条件随机场等。(Statistical learning is an important subject in the field of computer and application of this book comprehensively systematically introduces the main methods of statistical learning, especially the supervision method of study, including the perception, K neighbor method, naive bayesian method, decision tree, logistic regression, and the maximum entropy model, support vector machine (SVM), promotion methods, the EM algorithm, the hidden markov model and conditional random field, etc.)

说明：  漫威未来之战脚本源码,修改器,脚本,支持全部英雄修改,能量,力量,能量防御,力量防御修改.未来之战英雄属性修改脚本. 附所有英雄ID对照表.(mobirum, ganeguardian,ggScript)