We consider the problem of target localization by a network of passive sensors. When an unknown target emits an acoustic or a radio signal, its position can be localized with multiple sensors using the time difference of arrival (TDOA) information. In this paper, we consider the maximum likelihood formulation of this target localization problem and provide efficient convex relaxations for this nonconvex optimization problem.We also propose a formulation for robust target localization in the presence of sensor location errors. Two Cramer-Rao bounds are derived corresponding to situations with and without sensor node location errors. Simulation results confirm the efficiency and superior performance of the convex relaxation approach as compared to the existing least squares based approach when large sensor node location errors are present.
标签： 传感器网络
上传时间： 2016-11-27
上传用户：xxmluo
Standard transfer specification (STS) –Physical layer protocol for one-way numeric and magnetic card token carriers .
上传时间： 2017-02-04
上传用户：aarons大叔
1．Describe a Θ(n lg n)-time algorithm that, given a set S of n integers and another integer x, determines whether or not there exist two elements in S whose sum is exactly x. (Implement exercise 2.3-7.)
上传时间： 2017-04-01
上传用户：糖儿水嘻嘻
1．Describe a Θ(n lg n)-time algorithm that, given a set S of n integers and another integer x, determines whether or not there exist two elements in S whose sum is exactly x. (Implement exercise 2.3-7.) #include<stdio.h> #include<stdlib.h> void merge(int arr[],int low,int mid,int high){ int i,k; int *tmp=(int*)malloc((high-low+1)*sizeof(int)); int left_low=low; int left_high=mid; int right_low=mid+1; int right_high=high; for(k=0;left_low<=left_high&&right_low<=right_high;k++) { if(arr[left_low]<=arr[right_low]){ tmp[k]=arr[left_low++]; } else{ tmp[k]=arr[right_low++]; } } if(left_low<=left_high){ for(i=left_low;i<=left_high;i++){ tmp[k++]=arr[i]; } } if(right_low<=right_high){ for(i=right_low;i<=right_high;i++) tmp[k++]=arr[i]; } for(i=0;i<high-low+1;i++) arr[low+i]=tmp[i]; } void merge_sort(int a[],int p,int r){ int q; if(p<r){ q=(p+r)/2; merge_sort(a,p,q); merge_sort(a,q+1,r); merge(a,p,q,r); } } int main(){ int a[8]={3,5,8,6,4,1,1}; int i,j; int x=10; merge_sort(a,0,6); printf("after Merging-Sort:\n"); for(i=0;i<7;i++){ printf("%d",a[i]); } printf("\n"); i=0;j=6; do{ if(a[i]+a[j]==x){ printf("exist"); break; } if(a[i]+a[j]>x) j--; if(a[i]+a[j]<x) i++; }while(i<=j); if(i>j) printf("not exist"); system("pause"); return 0; }
上传时间： 2017-04-01
上传用户：糖儿水嘻嘻
The CommScope InstaPATCH® 360 and ReadyPATCH® solutions utilize a standards-compliant multi-fiber connector to provide high density termination capability. The connector is called an MPO (Multi-fiber Push On) connector by the standards. In many cases, multi-fiber connector products are referred to as MTP connectors. This document is intended to clarify the difference between the two terms – MPO and MTP.
上传时间： 2017-04-12
上传用户：asdfghjkl1234567890
Introduction jSMPP is a java implementation (SMPP API) of the SMPP protocol (currently supports SMPP v3.4). It provides interfaces to communicate with a Message Center or an ESME (External Short Message Entity) and is able to handle traffic of 3000-5000 messages per second. jSMPP is not a high-level library. People looking for a quick way to get started with SMPP may be better of using an abstraction layer such as the Apache Camel SMPP component: http://camel.apache.org/smpp.html Travis-CI status: History The project started on Google Code: http://code.google.com/p/jsmpp/ It was maintained by uudashr on Github until 2013. It is now a community project maintained at http://jsmpp.org Release procedure mvn deploy -DperformRelease=true -Durl=https://oss.sonatype.org/service/local/staging/deploy/maven2/ -DrepositoryId=sonatype-nexus-staging -Dgpg.passphrase=<yourpassphrase> log in here: https://oss.sonatype.org click the 'Staging Repositories' link select the repository and click close select the repository and click release License Copyright (C) 2007-2013, Nuruddin Ashr uudashr@gmail.com Copyright (C) 2012-2013, Denis Kostousov denis.kostousov@gmail.com Copyright (C) 2014, Daniel Pocock http://danielpocock.com Copyright (C) 2016, Pim Moerenhout pim.moerenhout@gmail.com This project is licensed under the Apache Software License 2.0.
上传时间： 2019-01-25
上传用户：dragon_longer
Description The L9352B is an integrated quad low-side power switch to drive inductive loads like valves used in ABS systems. Two of the four channels are current regulators with current range from 0 mA to 2.25 A. All channels are protected against fail functions. They are monitored by a status output.
标签： L9352B
上传时间： 2019-03-27
上传用户：guaixiaolong
Reconstruction- and example-based super-resolution (SR) methods are promising for restoring a high-resolution (HR) image from low-resolution (LR) image(s). Under large magnification, reconstruction-based methods usually fail to hallucinate visual details while example-based methods sometimes introduce unexpected details. Given a generic LR image, to reconstruct a photo-realistic SR image and to suppress artifacts in the reconstructed SR image, we introduce a multi-scale dictionary to a novel SR method that simultaneously integrates local and non-local priors. The local prior suppresses artifacts by using steering kernel regression to predict the target pixel from a small local area. The non-local prior enriches visual details by taking a weighted average of a large neighborhood as an estimate of the target pixel. Essentially, these two priors are complementary to each other. Experimental results demonstrate that the proposed method can produce high quality SR recovery both quantitatively and perceptually.
标签： Super-resolution Multi-scale Dictionary Single Image for
上传时间： 2019-03-28
上传用户：fullout
In this paper we present a classifier called bi-density twin support vector machines (BDTWSVMs) for data classification. In the training stage, BDTWSVMs first compute the relative density degrees for all training points using the intra-class graph whose weights are determined by a local scaling heuristic strategy, then optimize a pair of nonparallel hyperplanes through two smaller sized support vector machine (SVM)-typed problems. In the prediction stage, BDTWSVMs assign to the class label depending on the kernel density degree-based distances from each test point to the two hyperplanes. BDTWSVMs not only inherit good properties from twin support vector machines (TWSVMs) but also give good description for data points. The experimental results on toy as well as publicly available datasets indicate that BDTWSVMs compare favorably with classical SVMs and TWSVMs in terms of generalization
标签： recognition Bi-density machines support pattern vector twin for
上传时间： 2019-06-09
上传用户：lyaiqing
pcie3.0标准规范 1. INTRODUCTION 2. TRANSACTION LAYER SPECIFICATION 3. DATA LINK LAYER SPECIFICATION 4. PHYSICAL LAYER SPECIFICATION 5. POWER MANAGEMENT 6. SYSTEM ARCHITECTURE 7. SOFTWARE INITIALIZATION AND CONFIGURATION
标签： pcie3
上传时间： 2019-07-05
上传用户：bingshi
