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Description: adaptive mmse space-time multiuser detection algorithm.m是自适应MMSE空时多用户检测算法 dec multiuser.m是空时解相关多用户检测算法 cd multiuser.m是空时匹配滤波器 ber.m是误码率计算 conver.m是空时PN码产生文件-adaptive space-time multiuser detec tion is algorithm.m MMSE space-time adaptive multi-user detection algorithm dec multi user.m solution when space is multi-user detection algorithm cd multiuser.m was empty when matched filter ber.m error rate is calculated conver.m was empty at the PN code generated
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Size: 3351 |
Author: 陈永强 |
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Description: 频谱匹配滤波器检测 matlab
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Size: 2178 |
Author: 358990716@qq.com |
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Description: adaptive mmse space-time multiuser detection algorithm.m是自适应MMSE空时多用户检测算法 dec multiuser.m是空时解相关多用户检测算法 cd multiuser.m是空时匹配滤波器 ber.m是误码率计算 conver.m是空时PN码产生文件-adaptive space-time multiuser detec tion is algorithm.m MMSE space-time adaptive multi-user detection algorithm dec multi user.m solution when space is multi-user detection algorithm cd multiuser.m was empty when matched filter ber.m error rate is calculated conver.m was empty at the PN code generated
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Size: 3072 |
Author: 陈永强 |
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Description: 机动目标的跟踪问题一直是人们研究的重点，实现机动目标精确跟踪，首要解决的问题就是使所建立的目标运动模型与实际的目标运动模型匹配。目前常用的有多模型(MM)，交互式多模型(IMM)，切换模型等。多模型方法就是对一组具有不同机动模型分别进行Kalman滤波，最终的参数估计是各滤波器估计值的加权和；在多模型基础上，Shalom提出了交互式多模型方法，这一方法对无序目标的机动检测，显示了更好的鲁棒性和跟踪的稳定性；切换模型则是分别建立机动和非机动运动模型，利用机动检测实现在这两个模型之间的切换。一般来说，交互式多模型的跟踪性能较好。-mobile target tracking problem has been a focus of research and achieve precise maneuvering target tracking, the most pressing issue is to enable the establishment of the target model and the actual movement of the target model matching. At present, more commonly used model (MM), interactive multi-model (IMM), switching model. Multi-model approach is a group of different mobile models were Kalman filtering, The final parameter is the estimated value of the filter is estimated weighted; in the multi-model basis, Shalom made the interactive multi-model approach that the objectives of the motor disorder detection, better show the robustness and stability of the track; switching model is set up motorized and non-motorized sports model, the use of mobile testing to achieve in this model between
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Size: 207872 |
Author: zhangyun |
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Description: matlab 匹配滤波器，探地雷达目标检测,非常有用！-matlab matched filter!GPR targets detect!very useful!
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Size: 2048 |
Author: 王伟 |
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Description: 利用M函数仿真扩频通信系统。6个用户的CDMA的同步通信系统，每个用户利用L＝31的Gold码，进行扩频，信道为AWGN信道，接收端利用匹配滤波器进行检测。绘出当N＝10000个发射比特下，SNR＝0：15（dB）时的误码率曲线。
-M function simulation using Spread Spectrum Communication System. 6 simultaneous users of CDMA communication system, each user of the L = 31 the use of Gold codes for spread spectrum, channel for the AWGN channel, the receiving end to detect the use of matched filter. Drawn when N = 10000 bits of transmission, SNR = 0:15 (dB) when the bit error rate curve.
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Size: 1024 |
Author: 沈友俊 |
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Description: 根据雷达信号的时宽带宽乘积为常量, 不能兼顾作用距离和距离分辨率的原理, 使含有噪声的Chirp
信号经过匹配滤波器加以检测, 并对其进行了MATLAB 仿真。-According to radar signal bandwidth product of the time constant and can not take into account the role of the principle of distance and range resolution, so that noisy Chirp signal to be detected through the matched filter, and its conduct of the MATLAB simulation.
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Size: 605184 |
Author: gms |
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Description: 维纳匹配滤波器，在信号处理中，为了判断信号什么时候发生，维纳匹配滤波可以很好的检测信号是否发生，并在什么时候发生-wiener match fliter
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Size: 1024 |
Author: 于建波 |
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Description: 实现了用匹配滤波器对多用户信号中的期望用户进行检测-Achieved with a matched filter on the multi-user signal detection in the hope that users
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Size: 5120 |
Author: 黄博学 |
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Description: 匹配滤波器，信号检测，研究生课程作业，欢迎大家下载查阅！-pi pei
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Size: 297984 |
Author: 阿穆 |
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Description: 认知无线电频谱感知匹配滤波器检测仿真，选用FM信号，分析了虚警概率-Matched filter spectrum sensing cognitive radio simulation testing, the choice of FM signals, analysis of the probability of false alarm
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Size: 1024 |
Author: 秦楠楠 |
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Description: 介绍了一种基于神经网络白化匹配滤波器的QRS 波检测方法。我们用神经网络白化匹配滤波器来处
理ECG 信号的低频成分, 模拟其非线性及非稳态的特性。处理后的信号中含有ECG 中大部分高频成分, 让其通过
一线性匹配滤波器来检测QRS 波及其位置。对于大噪声的ECG 信号, 在匹配滤波器后加差分滤波, 取平方及滑动
平均等处理, 提高检测正确率。使用这种方法我们对M IT?B IH 心电信号数据库中噪声比较大的105号数据进行的
处理, 检测正确率为9912 。作为对比, 用数字带通滤波器检测, 正确率为9718 。-Introduced a whitening matched filter based on neural network of the QRS wave detection. We use neural networks to handle the whitening matched filter low frequency ECG signal to simulate the nonlinear and non-steady state characteristics. Processed ECG signal contains most of the high frequency components, let through a linear matched filter to detect the QRS wave and position. For large noise the ECG signal after the matched filter plus differential filter, such as taking the square and the moving average processing, improve the detection accuracy. Using this method we have M IT?B IH noise ECG database of 105 large data processing, testing rate was 9912 correct. In contrast, detection with digital band-pass filter, the correct rate of 9718 .
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Size: 266240 |
Author: 罗朝辉 |
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Description: 本论文概述了信号检测技术，如能量检测、匹配滤波器检测等，重点研究了循
环平稳检测法，并与能量检测法进行性能对比，仿真表明循环平稳检测性能明显
优于能量检测。论文讨论了循环平稳检测法检测统计量的选取，研究了循环谱峰
均比的特性，并对使用循环谱峰均比作为检测统计量的循环平稳检测法进行了仿
真，仿真表明使用循环谱峰均比作为检测统计量的循环平稳检测性能优于传统的
循环平稳检测法。-This paper outlines the signal detection techniques, such as energy detection, matched filter detection, focusing on the cyclostationary detection method and detection method and energy performance comparison, simulations show that the cyclostationary detection performance was significantly better than the energy detection. Paper discusses the detection assay cyclostationary statistics of the selected peak of the cycle than the characteristics and use of cycle peaks than as a test statistic of cyclostationary detection for simulation, the simulations show that the use of cycle peaks than as a test statistic of cyclostationary detection performance is superior to conventional cyclostationary detection.
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Size: 2318336 |
Author: 贾琼 |
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Description: 认知无线电是一种用于提高无线电通信频谱利用率的新的智能技术。 文章简述
了认知无线电的背景和概念，针对认知无线电的频谱感知能力，详细对比分析了四种频 谱检测技术：匹配滤波器法、能量检测法、循环平稳特性检测法和基于干扰的检测法，在 此基础上分析了当前频谱检测技术所面临的挑战。 最后探讨了干扰温度模型，并展望了 频谱检测技术的发展前景-cognitive radio networks
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Size: 7168 |
Author: w,k |
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Description: 认知无线电中频谱感知的几种检测方法，能量检测、匹配滤波器检测、循环特征检测-cognitive radio
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Size: 553984 |
Author: luyou |
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Description: 认知无线电中的匹配滤波器检测方法的matlab仿真程序-Cognitive radio matched filter detection method matlab simulation program
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Size: 1024 |
Author: 张皓源 |
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Description: 认知无线电频谱感知中的单用户频谱感知的主要三种方法：能量检测，循环平稳特征检测，匹配滤波器检测 的matlab实现的源代码-cognitive radio spectrum sensing：Energy detection, cyclostationary feature detection, matched filter detection 。matlab the source code
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Size: 4096 |
Author: 黄伟伟 |
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Description: 认识无线电 频谱感知 匹配滤波器检测 不同SNR下的结果-matched filter detection
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Size: 1024 |
Author: teng |
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Description: 编写MATLAB程序，讨论在 ??_0=5×〖10〗^(?5)的加性高斯白噪声环境中，利用匹配滤波器检测幅度为2，宽度为1ms的方波信号的情况(考虑取样时间为Ts=0.1ms)，测量匹配滤波器输入信号中心处与输出信号最佳取样处的SNR，绘出信号波形。(Write a MATLAB program, "10" discussed in the _0=5 * ^ (- 5) and Gauss white noise environment, using the matching detection filter amplitude is 2, the width of 1ms square wave signal condition (considering the sampling time is Ts=0.1ms), measuring the matched filter input signal and output signal at the center of the optimum sampling at SNR, draw the signal waveform.)
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Size: 12288 |
Author: Selena_01
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Description: 前已提出的频谱感知方法主要包括匹配滤波器检测、 能量检测、 循环平稳特征检测以及多分辨率频谱感知. 这些方法均为单节点感知方法.然而，在阴影和深度衰落情况下， 单个节点的感知结果并不可靠， 因此， 需要对多个节点的感知结果进行融合，以提高检测可靠性， 即协作感知技术. 文献采用“或” 准则对各个 CR 感知结果进行融合. 文献则提出了基于 D-S 证据理论的协作频谱感知算法，虽然该算法的性能比“或” 准则或“与”准则要好， 但需要存储大量历史信息， 算法的计算复杂度也很高. 文献中分析了采用似然比检测(likelihood ratio test， LRT) 的软判决与采用“与” 准则的硬判决的性能， 结果表明采用软判决的协作感知性能更优(Previously proposed spectrum sensing methods mainly include matched filter detection, energy detection, cyclostationary feature detection and multi-resolution spectrum sensing. These methods are all single node sensing methods. However, in the case of shadow and deep fading, the sensing results of single node are not reliable, so, It is necessary to fuse the sensing results of multiple nodes to improve the detection reliability, i.e. cooperative sensing technology. In the literature, "or" criterion is used to fuse the CR sensing results. In the literature, a cooperative spectrum sensing algorithm based on D-S evidence theory is proposed. Although the performance of the algorithm is better than "or" criterion or "and" criterion, a large amount of historical information needs to be stored, The computational complexity of the algorithm is also very high. In the literature, the performance of the soft decision based on the likelihood ratio test)
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Size: 6144 |
Author: UU仔 |
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