Location:
Search - monitor matlab
Search list
Description: 一个用小波奇异点监测法来监测心电信号R波的例子，可用在其他信号的奇异点监测上。-a singular point wavelet monitoring method to monitor ECG R-wave example, other signals can be used in the singular point monitoring.
Platform: |
Size: 5120 |
Author: 付荣申 |
Hits:
Description: tcpip监控程序,监听某个端口传来的tcpip数据-TCPIP monitoring program, a monitor port data came TCPIP
Platform: |
Size: 64512 |
Author: |
Hits:
Description: 假设在一个ad hoc网络中，移动节点的发射功率PTx总是恒定的。要发送数据的移动节点总是先监听信道，测量接收到的信号功率X，其中X= I + N, I为接收到的干扰，N是噪声。移动节点只有在X＜INThre时，才可以发射。式中，INThre为背景噪声门限。
在仿真中，我们规定每个移动节点的发射功率是常数，PTx = 1W；接收节点接收机的灵敏度Smin = -80 dBm；信号质量 min = 2 dB；系统的背景噪声门限INThre = 1.2e-10。
-Assuming in an ad hoc network, mobile node s transmission power is always constant PTX. To send data to the mobile node always monitor channel, measuring the received signal power X, which X = I+ N, I was received interference, N is the noise. Mobile node only when X <INThre when it is fired. Where, INThre threshold for background noise. In the simulation, we require that each mobile node s transmission power is constant, PTx = 1W receiver node receiver sensitivity Smin =-80 dBm signal quality
Platform: |
Size: 7168 |
Author: 飞 |
Hits:
Description: 根据有无固定基础设施，无线局域网又可分为BSS (Basic Service Set)和IBSS (Independent Basic Service Set)。我们要研究的ad hoc网络属于后者。假设在一个ad hoc网络中，移动节点的发射功率PTx总是恒定的。要发送数据的移动节点总是先监听信道，测量接收到的信号功率X，其中X= I + N, I为接收到的干扰，N是噪声。移动节点只有在X＜INThre时，才可以发射。式中，INThre为背景噪声门限。
在仿真中，我们规定每个移动节点的发射功率是常数，PTx = 1W；接收节点接收机的灵敏度Smin = -80 dBm；信号质量 min = 2 dB；系统的背景噪声门限INThre = 1.2e-10。
-According to the availability of fixed infrastructure, wireless local area network can be divided into BSS (Basic Service Set) and IBSS (Independent Basic Service Set). We have to study the ad hoc network belong to the latter. Assuming in an ad hoc network, mobile node s transmission power is always constant PTX. To send data to the mobile node always monitor channel, measuring the received signal power X, which X = I+ N, I was received interference, N is the noise. Mobile node only when X <INThre when it is fired. Where, INThre threshold for background noise. In the simulation, we require that each mobile node s transmission power is constant, PTx = 1W receiver node receiver sensitivity Smin =-80 dBm signal quality
Platform: |
Size: 7168 |
Author: 何炳钦 |
Hits:
Description: On-Line MCMC Bayesian Model Selection
This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
-On-Line MCMC Bayesian Model Selection
This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar-xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
Platform: |
Size: 16384 |
Author: 徐剑 |
Hits:
Description: In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar -xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets.
-In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar-xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets.
Platform: |
Size: 197632 |
Author: 晨间 |
Hits:
Description: This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.-This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar-xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
Platform: |
Size: 220160 |
Author: 晨间 |
Hits:
Description: This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar -xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
-This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar-xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
Platform: |
Size: 348160 |
Author: 晨间 |
Hits:
Description: 基于ARM7的便携式心电监护仪及心电分析的研究-ARM7-based portable ECG monitor and ECG analysis
Platform: |
Size: 2823168 |
Author: 江山 |
Hits:
Description: 小护士脉搏监护仪全套系统，包括程序，电路图，波形，参考资料等，还有和PC的matlab通信部分，一应俱全。-Small nurses monitor the pulse of a full set of systems, including procedures, circuit diagrams, waveform, reference materials, as well as and the PC part of matlab communication services.
Platform: |
Size: 23508992 |
Author: zhanghongwei |
Hits:
Description: 卡尔曼滤波非线性识别,土木工程
健康监测，损伤识别，-karman，civil engineering
identification,health of structure monitor
Platform: |
Size: 88064 |
Author: xiaoxiang |
Hits:
Description: 绘制眼图的matlab程序,可以用于通信系统中传输质量的监测。-Matlab draw the eye diagram of the procedure can be used in communication systems to monitor the transmission quality.
Platform: |
Size: 2048 |
Author: Frank Chan |
Hits:
Description: 数字视频监控系统代表了监控行业的未来发展方向，蕴藏着巨大的商机和
经济效益，成为目前信息产业中颇受关注的数字化产品。特别是近年来，随着
技术的进步和社会经济的不断发展，客观上对监控系统的准确性、有效性和方
便性提出了更高要求。主要体现在：需要实施视频监控的范围更加广阔，达到
点多面广；要求监控系统与管理信息系统、网络系统结合，实现对大量视频数
据的压缩存储、传输和自动处理，从而达到资源共享，为各级管理人员和决策
者提供方便、快捷、有效的服务。可见基于 DSP 和小波压缩技术的远程音频视
频监控具有现实意义和广阔前景。-Digital Video Surveillance System to monitor represents the future direction of the industry, there are enormous business opportunities and
Economic benefits of the information industry has become quite concerned about the digital product. In recent years, with the
Technological progress and socio-economic development, the objective of monitoring system on the accuracy, effectiveness and side
Will be put forward higher requirements. Mainly embodied in: the need for the implementation of video surveillance broader scope, reaching
Points wide require monitoring system and management information systems, network systems, to achieve a number of the large number of video
According to the compressed storage, transmission and automatic processing, so as to achieve resource sharing, for all levels of management and decision-making
Provide convenient, speedy and efficient service. Can be seen based on the DSP and wavelet compression technology as the long-range audio
Frequency of
Platform: |
Size: 588800 |
Author: 耿耿 |
Hits:
Description: 麻省MIT基于Matlab开发的GPS监测地球板块速度的速度场显示程序-Massachusetts, MIT developed Matlab-based GPS to monitor the speed of the Earths plate velocity field display program
Platform: |
Size: 449536 |
Author: 阿发 |
Hits:
Description: Negative Selection Agorithm
1. we have a signal which we ll monitor
2. we produce lymphocytes - length lyphocyte as a signal, we take random numbers
3. NSA... we check that lymphocyte is different from signal, if not we random another
4. now we monitor signal, if any value of signal is the same or nearest to lyphocyte - we have anomaly. -Negative Selection Agorithm
1. we have a signal which we ll monitor
2. we produce lymphocytes- length lyphocyte as a signal, we take random numbers
3. NSA... we check that lymphocyte is different from signal, if not we random another
4. now we monitor signal, if any value of signal is the same or nearest to lyphocyte- we have anomaly.
Platform: |
Size: 8192 |
Author: Tom |
Hits:
Description: 视频监视程序，可以监视摄像头拍摄的内容是否发生变化-Video surveillance program, you can monitor whether the contents of the camera shot changes
Platform: |
Size: 1024 |
Author: 朱青祥 |
Hits:
Description: matlab视频监控程序，10秒拍一张照片。-matlab video surveillance program, 10 seconds a photo shoot.
Platform: |
Size: 9216 |
Author: hooget |
Hits:
Description: To improve the boiler drum level control system of a power plant, the three challenging issues encountered include (1)
effect of ‘‘false water level’’, (2) controller parameter mismatches due to variant working conditions and (3) signal noise
caused by uncertainties of drum level. In this paper, based on analyses of the drum level signal, an adaptive derivative
action is presented to monitor steam flow, and thus, the effect of ‘‘false water level’’ is weakened. The uncertainties of
parameter mismatches and noise are predicted by developing a Grey predictor based algorithm (GPBA). In order to
resolve the three problems and further control performance, an adaptive technique is combined with the GPBA to develop
an adaptive Grey predictor based method. Finally, concrete simulations give that the proposed method has obvious superiority
over conventional methods.
Platform: |
Size: 164864 |
Author: karthikeyan |
Hits:
Description: 基于matlab的摄像头监控程序，功能较强-camera monitor matlab
Platform: |
Size: 27648 |
Author: slim |
Hits:
Description: 检测识别视频中的动态物体，比如人体和车辆，可用于监控处理-Detection and identification of dynamic objects in the video, such as humans and vehicles, can be used to monitor treatment
Platform: |
Size: 676864 |
Author: seanwillian |
Hits: