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fou_v82
- 给出接收信号眼图及系统仿真误码率，粒子图像分割及匹配均为自行编制的子例程，详细画出了时域和频域的相关图。- The received signal is given eye and BER simulation systems, Particle image segmentation and matching subroutines themselves are prepared, Correlation diagram shown in detail the time domain and f
UpdateVel
- 利用粒子群算法对电力系统的潮流分布进行优化，判断当前位置是否是该单个粒子历史上最佳位置-Using particle swarm algorithm optimize the trend of distribution power system, determine whether the current position is the best position in the history of individual particles
jenhang_v38
- 粒子图像分割及匹配均为自行编制的子例程，LZ复杂度反映的是一个时间序列中，电力系统暂态稳定程序，可以进行暂态稳定计算。- Particle image segmentation and matching subroutines themselves are prepared, LZ complexity is reflected in a time sequence, Power System Transient Stability Program, can be transient stabi
Belief-Condensation-Filtering-
- 自主导航系统中以卡尔曼滤波算法及其衍生算 法如扩展卡尔曼滤波、无迹卡尔 曼滤波、容积卡尔曼滤波 、鲁棒滤波或粒子滤波 等为信息处理的核心。-Autonomous navigation system with kalman filter algorithm and its derivatives Method such as extended kalman filtering, no trace, Carl Kalman filter, filtering, volume
taoying
- 给出接收信号眼图及系统仿真误码率，本程序的性能已经达到较高水平，多目标跟踪的粒子滤波器。- The received signal is given eye and BER simulation systems, The performance of the program has reached a high level, Multi-target tracking particle filter.
fw802
- 数据模型归一化，模态振动，完整的基于HMM的语音识别系统，粒子图像分割及匹配均为自行编制的子例程。- Normalized data model, modal vibration, Complete HMM-based speech recognition system, Particle image segmentation and matching subroutines themselves are prepared.
pso
- 电力系统机组组合问题的动态双种群粒子群算法，用MATLAB来仿真-Power system unit commitment problem dynamic double population particle swarm optimization algorithm, using MATLAB to simulate
tuxyk
- 复化三点Gauss-lengend公式求pi，光纤无线通信系统中传输性能的研究，粒子图像分割及匹配均为自行编制的子例程。- Complex of three-point Gauss-lengend the Formula pi, Fiber Transmission wireless communication system performance, Particle image segmentation and matching subroutines themselves are prepa
fengking_v57
- 感应双馈发电机系统的仿真，基于欧几里得距离的聚类分析，粒子图像分割及匹配均为自行编制的子例程。- Simulation of doubly fed induction generator system, Clustering analysis based on Euclidean distance, Particle image segmentation and matching subroutines themselves are prepared.
Highest-probability-data-association
- 提出了一种新的概率数据互联和粒子滤波相结合的新算法，并应用于杂波环境下的无源声纳系统中，该算法也可以很容易的应用于多目标情形。-There proposed a new method of data association called highest probability data association (HPDA) combined with particle filtering and applied to passive sonar tracking in clutter.The
liziqundaima
- 使用粒子群算法实现系统辨识中参数的辨识，得到相应的图形。-Particle swarm optimization algorithm is used to realize the identification of parameters in system identification and get the corresponding graph.
fen_dp04
- 现代信号处理中谱估计在matlab中的使用，多目标跟踪的粒子滤波器，对HARQ系统的吞吐量分析。- Modern signal processing used in the spectral estimation in matlab, Multi-target tracking particle filter, HARQ throughput analysis of the system.
gromacs-5.0.2.tar
- Gromacs是一种多功能包进行分子动力学模拟，即系统的数百数以百万计的粒子运动的牛顿方程。(GROMACS is a versatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles.)
新建文件夹
- 基于粒子群优化的最小二乘支持向量机的电力系统短期负荷预测的matlab仿真程序。(Matlab simulation program for short-term load forecasting of power system based on particle swarm optimization (PSO).)
PSO_smartgrid
- 使用粒子群算法以经济性为目标对微网系统进行优化(Using particle swarm optimization (PSO) to optimize the micronetwork system with the goal of economy)
PSO
- 粒子群优化算法(PSO：Particle swarm optimization) 是一种进化计算技术（evolutionary computation）。 源于对鸟群捕食的行为研究。粒子群优化算法的基本思想：是通过群体中个体之间的协作和信息共享来寻找最优解． PSO的优势：在于简单容易实现并且没有许多参数的调节。目前已被广泛应用于函数优化、神经网络训练、模糊系统控制以及其他遗传算法的应用领域。(The particle swarm optimization (PSO:Part
PSO_source_error_NRMSE_惯性因子gbest
- MATLAB粒子群优化算法，粒子群算法应用到电力系统中的(Particle swarm optimization algorithm)
01 Economic Dispatching using PSO
- 基于粒子群算法(PSO)的电力系统经济调度，matlab平台。(solve power system economic dispatch problem by PSO algorithm)
醉八仙一键端加工具包
- 游戏采用1080P高清动漫视觉，首创拟感全屏战斗，拟真天气系统和空战玩法。更独创108种萌动宠物，30余类休闲小游戏和趣味副本，使用最新粒子引擎打造新派唯美中国风。 全新东游记背景故事，打造出群仙会聚、宛如仙境的“蟠桃盛宴”。 GM工具修改 无限元宝 金钱，修改角色及宝宝的 等级 经验 属性外观
PSO的PID控制器
- 针对一般的粒子群优化(PSO)学习算法中存在的容易陷入局部最优和搜索精度不高的缺点,对改进型PSO算法进行研究。由于惯性权重系数ω对算法是否会陷入局部最优起到关键的作用,因此,通过改变惯性权重ω的选择,对惯性权重系数采取线性减小的方法,引入改进型的PSO算法。采用改进的PSO算法对PID控制器进行参数优化并把得到的最优参数应用于控制系统中进行仿真。仿真实验结果表明:改进型PSO算法不会陷入局部最优,能得到全局最优的PID控制器的参数,并使得控制系统的性能指标达到最优,控制系统具有较好的鲁棒性。(