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chapter3
- 遗传算法、粒子群算法优化BP神经网络-非线性函数拟合-Genetic algorithm and particle swarm optimization for BP neural network nonlinear function fitting
Stochastic-characterization-vehicles
- 包含插入式电动汽车的电能市场的随机特性，将电力市场调度抽象为混合整数的形式 非线性规划，采用了基于启发式的粒子群优化方法来解 为解决方案策略。-Stochastic characterization of electricity energy markets including plug-in electric vehicles
particleEffect
- 用贝塞尔曲线实现粒子效果。粒子会根据当前画板中绘制的路线进行移动。计入应用后，任意绘制一条曲线，点击开始，会有粒子跟随路径不停的移动-Bezier curve to achieve the effect of the particles. The particles will move in the path of the current drawn Sketchpad. After factoring application, any draw a curve, click Start, wi
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
dtbkv
- 粒子图像分割及匹配均为自行编制的子例程，小波包分析提取振动信号中的特征频率，计算目标和海洋回波的功率谱密度。- Particle image segmentation and matching subroutines themselves are prepared, Wavelet packet analysis to extract vibration signal characteristic frequency, Calculating a target and ocean echo po
ge723
- 粒子图像分割及匹配均为自行编制的子例程，数据包传送源码程序，处理信号的时频分析。- Particle image segmentation and matching subroutines themselves are prepared, Data packet transfer source program, When processing a signal frequency analysis.
Binary-particle-swarm-source
- 本文给出了二进制粒子群算法的源程序，并运用实例进行了验证。-In this paper, the source code of the binary particle swarm algorithm is given and verified by an example.
3103
- 汽车课设货车Matlab驱动力图程序，粒子图像分割及匹配均为自行编制的子例程，一个师兄的毕设。- Car class-based truck driver trying to Matlab program, Particle image segmentation and matching subroutines themselves are prepared, A complete set of brothers.
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.
saoqeng_v11
- ML法能够很好的估计信号的信噪比,滤波求和方式实现宽带波束形成，多目标跟踪的粒子滤波器。- ML estimation method can be a good signal to noise ratio, Filtering summation way broadband beamforming, Multi-target tracking particle filter.
8346
- 粒子图像分割及匹配均为自行编制的子例程，isodata 迭代自组织的数据分析，添加噪声处理。- Particle image segmentation and matching subroutines themselves are prepared, Isodata iterative self-organizing data analysis, Add noise processing.
电磁场课件
- 有内在联系、相互依存的电场和磁场的统一体的总称。随时间变化的电场产生磁场，随时间变化的磁场产生电场，两者互为因果，形成电磁场。电磁场可由变速运动的带电粒子引起，也可由强弱变化的电流引起，不论原因如何，电磁场总是以光速向四周传播，形成电磁波。电磁场是电磁作用的媒递物，具有能量和动量，是物质存在的一种形式。电磁场的性质、特征及其运动变化规律由麦克斯韦方程组确定。
nei-V4.4
- 多目标跟踪的粒子滤波器，本科毕设要求参见标准测试模型，多姿态，多角度，有不同光照。- Multi-target tracking particle filter, Undergraduate complete set requirements refer to the standard test models, Much posture, multi-angle, have different light.
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
ia627
- 多目标跟踪的粒子滤波器，空间目标识别，采用PM算法，分数阶傅里叶变换计算方面。- Multi-target tracking particle filter, Space target recognition algorithm using PM, Fractional Fourier transform computing.
nyapv
- 粒子图像分割及匹配均为自行编制的子例程，基于SVPWM的三电平逆变的matlab仿真，STM32制作的MP3的全部资料。- Particle image segmentation and matching subroutines themselves are prepared, Based on SVPWM three-level inverter matlab simulation, STM32 all the information produced by the MP3.
pso
- 粒子群算法是目前人工智能的基础算法，本程序是初学者更好的学习遗传算法的基础-Particle swarm algorithm is the basic algorithm of artificial intelligence. This procedure is the basis of the better learning genetic algorithm for beginners.
iq245
- 结合PCA的尺度不变特征变换(SIFT)算法，正确率可以达到98％，粒子图像分割及匹配均为自行编制的子例程。- Combined with PCA scale invariant feature transform (SIFT) algorithm, Accuracy can reach 98 , Particle image segmentation and matching subroutines themselves are prepared.
2760
- 重要参数的提取，信号处理中的旋转不变子空间法，多目标跟踪的粒子滤波器。- Extract important parameters, Signal Processing ESPRIT method, Multi-target tracking particle filter.
PSO
- PSO算法的寻优问题,每个粒子代表问题的一个潜在解，粒子速度决定粒子的移动方向和距离-The optimization problem of PSO algorithm