搜索资源列表
DV_HOP_MATLAB
- 无线传感器网络dv-hop定位算法仿真 仿真工具是matlab-Dv-hop wireless sensor network localization algorithm simulation tool is matlab simulation
Kalman_Filter
- 利用kalman滤波算法仿真二自由度机器人对平面点的定位(机器人视觉伺服)-Kalman filtering algorithm using two degrees of freedom robot simulation of planar point location (robot visual servo)
Sensor-network
- 传感器网络的粒子群优化定位算法,有多篇经典文献,并有仿真实例。-Sensor network of particle swarm optimization localization algorithm, have more than paper classical literature, and a simulation example.
the-simulation-examples
- 基于差分进化和粒子群优化算法的混合优化算法,基于差分进化算法的定位算法,及其仿真。-Based on differential evolution and the particle swarm optimization algorithm hybrid optimization algorithm, evolutionary algorithm based on difference of localization algorithm, and its simulation.
the-simulation-and-examples
- 传感器网络的粒子群优化定位算法,及其基于差分进化算法的定位算法,带有2个simulink仿真。-Sensor network of particle swarm optimization localization algorithm, and its evolution algorithm based on difference of localization algorithm, with two simulink.
DV-hop
- 一种基于DV-hop的Ad Hoc网络定位算法,采用matlab仿真 -DV Based Positioning in Ad Hoc Networks,matlab simulation
DS18B20
- 本书系统地介绍了图像处理与识别的基本原理、典型方法和实用技术。全书共分12章,第1章-第6章是图像处理与识别的基础内容,包括图像科学综述、MATLAB语言图像编程、图像增强、图像分割、图像特征提取和图像识别;第7章-第10章是图像处理与识别的工程实例,涵盖了医学图像处理、文字识别和自导引小车路径识别等应用实例,并结合理论算法,提供了大量MATLAB代码程序,以帮助读者掌握如何使用MATLAB语言快速进行算法的仿真、调试和估计等方法。第11章-第12章,是两个综合性较强的实例,分别足Visual
matlab
- 用四元十字阵做被动声定位算法设计,现在是用matlab神经网络工具箱构建RBF神经网络然后仿真显示图形-With a four-element Array do passive acoustic localization algorithm design, now using matlab neural network toolbox and then build on RBF neural network simulation display graphics
RBF-neural-network
- 用四元十字阵做被动声定位算法设计,现在是用matlab神经网络工具箱构建RBF神经网络然后仿真显示图形-With a four-element Array do passive acoustic localization algorithm design, now using matlab neural network toolbox and then build on RBF neural network simulation display graphics
PARTICLE-FILTER-ISSUES
- 针对基于贝叶斯原理的序贯蒙特卡罗粒子滤波器出现退化现象的原因, 以无敏粒子滤波(U PF)、辅助粒子滤波 (A S IR) 及采样重要再采样(S IR) 等改进的粒子滤波算法为例, 对消除该缺陷的关键技术(优化重要密度函数及再采样) 进行了 分析研究。说明通过提高重要密度函数的似然度、引进当前测量值、预增和复制大权值粒子等方式, 可以有效改善算法性能。 最后通过对一无源探测定位问题进行仿真, 验证了运用该关键技术后, 算法的收敛精度和鲁棒性得到进一步增强。- Abstract:W e
CalculateUserPosition
- gps全球定位系统算法仿真,定位用户位置Matlab程序-GPS global positioning system (GPS) algorithm simulation, locate user s location Matlab program
kalman1
- gps全球定位系统的用户位置定位仿真程序,使用卡尔曼滤波算法-Global positioning system (GPS) user position location simulation program, using kalman filtering algorithm
knn
- 经典的分类算法,可以完成基本的分类。。。(Classic classification algorithm, you can complete the basic classification...)
ABSO
- 应用fluent仿真软件生成湍流烟羽环境下,应用头脑风暴优化算法气味源定位程序(Using fluent simulation software to generate turbulent plume environment, the application of brainstorming algorithm, odor source localization program)
WUIPSO
- 应用结合风速信息的带电粒子群算法,实现在fluent仿真环境下气味源定位代码(Applying the charged particle swarm algorithm combined with wind speed information, the odor source localization code is implemented in the fluent simulation environment)
AACO
- 应用结合逆风搜索的蚁群算法,实现fluent仿真环境下气味源定位(Using upwind search ant colony algorithm to realize odor source localization in fluent simulation environment)