搜索资源列表
SensorAnalysis
- 一组仪器性能分析程序，分别计算仪器的线性度、迟滞、符合度、重复性。其中M_repeatability与M_bessel一起使用计算重复性。具体算法参考《传感器技术及应用》樊尚春著。-equipment performance analysis procedures, the machines were calculated linearity, hysteresis, compliance and reproducibility. M_repeatability M_bessel which t
MQJ
- 一种倾角传感器的串口通讯实例，值得一看。-angle sensor of a serial communication example, an eye-catcher.
WiSNAP
- MatLab图像传感器网络仿真平台WiSNAP，非常好用和清晰-MatLab image sensor network simulation platform WiSNAP very useful and clear
sense-3.0.3-windows
- 大名鼎鼎的传感器网络仿真实验室平台SENSE-famous sensor network laboratory simulation platform SENSE
gridsim2
- SLAM Gridsim use with sparer sensor
1
- stitching for wireless sensor network
scp-stack-1.0.tar
- SCP-MAC is an MAC protocol designed for wireless sensor networks.
brdf
- 基于半无限均质分层介质的双向反射率函数模型（Mishchenko）的精确数值解，为Fortran语言代码。该均匀介质由任意形状，随机取向的颗粒构成。该双向反射率分布函数适用于土壤和雪/冰。文件spher.f 借助于Lorenz-Mie理论计算多分散球形颗粒的Legendre扩散系数。文件refl.f 计算反射率函数的傅立叶组分。而interp.f 计算任意太阳—传感器条件下双向反射率函数。-Semi-infinite homogeneous layered media based on bi-d
MLC
- this program classify image that take with TM sensor to 3 class using maximumlikelihood method. ENJOY it-this program classify image that take with TM sensor to 3 class using maximumlikelihood method. ENJOY it...
zuixiaoercheng2
- 多传感器数据融合系统中时间配准算法分析，最小二乘发算法-sensor time registration
D
- dijkstra routing algorithm in the wireless sensor network
SBJSQ
- VB6编写，汽车车速传感器输出速比计算软件，有RC滤波器计算功能。-VB6 for the vehicle speed sensor output speed ratio calculation software, the RC filter calculation.
paper1
- 基于点割集的无线带状传感网分布式寿命预测算法.pdf-Based the cutset wireless ribbon sensor network distributed life prediction algorithm. Pdf
Prim_heuristic_16_nodes
- A Prim s variation for use on Wireless Sensor Networks. We choose as next node to add to the MST, the node with max. residual energy.
A-Smart-Current-Sensor
- 一种新式的非接触性能的传感器，能广泛采集电流电压信息，应用前景广阔-A new type of sensor for non-contact performance, broad collection of current and voltage information, and broad application prospects
music1
- A Sparse Signal Reconstruction Perspective for Source Localization With Sensor Arrays Dmitry Malioutov, Student Member, IEEE, Müjdat Ç etin, Member, IEEE, and Alan S. Willsky, Fellow, I-A Sparse Signal Reconstruction Perspective for Source
Fusion-based-Sensor-Placement
- 论文 在使用无线传感器网络进行目标检测时,如何布置尽可能少的传感器节点而同时实现高的正确检测概率和 低的误警率,是关键问题之一。采用数据融合技术,能实现传感器节点之间的协同,从而大幅提高目标检测精度。提 出了用于目标检测的精度模型,分析了数据融合半径与传感器节点密度之间的关系,设计聚类方法将目标点组织成布 置单元,从高密度单元到低密度单元布置传感器节点覆盖目标区域。仿真结果表明,算法在保证检测精度的同时能有 效减少所使用的传感器节点数目。 - Sensor placeme
shuzu_ceshi
- 附件中提供了一种数组剔除方法，可以有效的消除数组中的冗余数据，另一方面在传感器节点选择中可以剔除已用多个节点-Annex provides an array of excluded methods, can effectively eliminate redundant data in the array, the other in the sensor node selection has been used in more than one node can be removed
sensor-networks
- 无线传感器网络节点查找与信息传递算法，谣传路由算法仿真-Wireless sensor network nodes and information transmission algorithm to find
Body-Area-Sensor-Networks
- Health monitoring is a wide and expanding area of application of wireless sensor networks. This paper presents the Distance Aware Relaying Energy efficient DARE protocol used in wireless sensor network applications.