This paper presents a modified Root-MUSIC algorithm by which the signal DOA estimation performance can be improved when the snapshot number is limited. The operation principlesof this algorithm are described in detail...This paper presents a modified Root-MUSIC algorithm by which the signal DOA estimation performance can be improved when the snapshot number is limited. The operation principlesof this algorithm are described in detail. It is also pointed out theoretically that this is equivalentto have increased the snapshot number and can make the DOA estimation better. Finally, somesimulating results to verify the theoretical analyses are presented.展开更多
In this paper, we consider a MUSIC algorithm for locating point-like scatterers contained in a sample on flat substrate. Based on an asymptotic expansion of the scattering amplitude proposed by Ammari et al., the reco...In this paper, we consider a MUSIC algorithm for locating point-like scatterers contained in a sample on flat substrate. Based on an asymptotic expansion of the scattering amplitude proposed by Ammari et al., the reconstruction problem can be reduced to a calculation of Green function corresponding to the background medium. In addition, we use an explicit formulation of Green function in the MUSIC algorithm to simplify the calculation when the cross-section of sample is a half-disc. Numerical experiments are included to demonstrate the feasibility of this method.展开更多
On account of the traditional multiple signal classification(MUSIC)algorithm has poor performance in time delay estimation under the condition of small sampling data and low SNR.In this paper,the traditional MUSIC alg...On account of the traditional multiple signal classification(MUSIC)algorithm has poor performance in time delay estimation under the condition of small sampling data and low SNR.In this paper,the traditional MUSIC algorithm is improved.The algorithm combines the idea of spatial smoothing,constructs a new covariance matrix using the covariance information of the measurement data,and constructs a weighted value using the modified noise eigenvalues to weight the traditional estimation spectrum.Simulation results show that the improved algorithm has steeper spectral peaks and better time delay resolution under the condition of inaccurate path number estimation.The time delay estimation accuracy of this algorithm is higher than that of the traditional MUSIC algorithm and the improved SSMUSIC algorithm under the conditions of small sampling data and low SNR.展开更多
In this paper,a time-frequency associated multiple signal classification(MUSIC)al-gorithm which is suitable for through-wall detection is proposed.The technology of detecting hu-man targets by through-wall radar can b...In this paper,a time-frequency associated multiple signal classification(MUSIC)al-gorithm which is suitable for through-wall detection is proposed.The technology of detecting hu-man targets by through-wall radar can be used to monitor the status and the location information of human targets behind the wall.However,the detection is out of order when classical MUSIC al-gorithm is applied to estimate the direction of arrival.In order to solve the problem,a time-fre-quency associated MUSIC algorithm suitable for through-wall detection and based on S-band stepped frequency continuous wave(SFCW)radar is researched.By associating inverse fast Fouri-er transform(IFFT)algorithm with MUSIC algorithm,the power enhancement of the target sig-nal is completed according to the distance calculation results in the time domain.Then convert the signal to the frequency domain for direction of arrival(DOA)estimation.The simulations of two-dimensional human target detection in free space and the processing of measured data are com-pleted.By comparing the processing results of the two algorithms on the measured data,accuracy of DOA estimation of proposed algorithm is more than 75%,which is 50%higher than classical MUSIC algorithm.It is verified that the distance and angle of human target can be effectively de-tected via proposed algorithm.展开更多
This paper gives a MUSIC signal DOA estimation algorithm based on the modified high-order cumulant matrix which is constructed by the recieved data and their conjugate rearrangements. When the snapshot number is limit...This paper gives a MUSIC signal DOA estimation algorithm based on the modified high-order cumulant matrix which is constructed by the recieved data and their conjugate rearrangements. When the snapshot number is limited, this algorithm can improve the signal DOA estimation performances obviously, and its computational complexity scarcely increases. Finally, some simulation results to verify the theoretical analyses are presented.展开更多
Multichannel biomagnetometers can be used to measure the spatio temporal magnetic field produced by neural activity in a human brain. The measured data are usually contaminated by noise and some artifact signals. Thes...Multichannel biomagnetometers can be used to measure the spatio temporal magnetic field produced by neural activity in a human brain. The measured data are usually contaminated by noise and some artifact signals. These artifact signals may be caused by heart beats or eye blinks. Actually, these artifact signal sources are also bioelectric activities. In this paper, we demonstrate the effectiveness of MEG MUSIC algorithm for eliminating the artifacts. In the paper, the artifact fields are not considered as noise but as signals that have a linear relationship with their bioelectric source activities. Computer simulations demonstrate that for the localization of sources distributed in the cortical region, the MEG MUSIC algorithm is also efficient under the presence of the artifacts.展开更多
准确测量管道介质声速有助于分析介质的密度和组分,而传统的声速测量方法重复性低、鲁棒性差。为了实现介质声速的准确测量,首先,基于管道一维声波理论推导出线阵列传感器在管道轴向位置的声信号模型,介绍了空气与水的理论声速计算公式...准确测量管道介质声速有助于分析介质的密度和组分,而传统的声速测量方法重复性低、鲁棒性差。为了实现介质声速的准确测量,首先,基于管道一维声波理论推导出线阵列传感器在管道轴向位置的声信号模型,介绍了空气与水的理论声速计算公式以及不同管材、管径和壁厚对声速衰减的影响;其次,采用MUSIC(multiple signal classification)波束形成算法将多通道时域数据转换至波数频率域,呈现出斜率与声速相关的“声学脊”;最后,使用DN50不锈钢管道分别在水和空气流量标准装置上进行声速测量实验,与理论数据相比,水中声速的相对误差为1.61%,重复性为0.45%,空气中声速的相对误差为0.59%,重复性为1.27%。结果表明MUSIC算法可准确测量管道一维声波的介质声速。展开更多
This article describes the development of an application for generating tonal melodies. The goal of the project is to ascertain our current understanding of tonal music by means of algorithmic music generation. The me...This article describes the development of an application for generating tonal melodies. The goal of the project is to ascertain our current understanding of tonal music by means of algorithmic music generation. The method followed consists of four stages: 1) selection of music-theoretical insights, 2) translation of these insights into a set of principles, 3) conversion of the principles into a computational model having the form of an algorithm for music generation, 4) testing the “music” generated by the algorithm to evaluate the adequacy of the model. As an example, the method is implemented in Melody Generator, an algorithm for generating tonal melodies. The program has a structure suited for generating, displaying, playing and storing melodies, functions which are all accessible via a dedicated interface. The actual generation of melodies, is based in part on constraints imposed by the tonal context, i.e. by meter and key, the settings of which are controlled by means of parameters on the interface. For another part, it is based upon a set of construction principles including the notion of a hierarchical organization, and the idea that melodies consist of a skeleton that may be elaborated in various ways. After these aspects were implemented as specific sub-algorithms, the device produces simple but well-structured tonal melodies.展开更多
实际变压器局部放电定位过程中放电源数目是未知的,常利用传统高分辨波达方向(direction of arrival,DOA)估计算法解决放电定位问题,但在信源数欠估计、过估计情况下存在定位精度低、误差大的问题。为此,本文提出了一种基于改进盖氏圆(g...实际变压器局部放电定位过程中放电源数目是未知的,常利用传统高分辨波达方向(direction of arrival,DOA)估计算法解决放电定位问题,但在信源数欠估计、过估计情况下存在定位精度低、误差大的问题。为此,本文提出了一种基于改进盖氏圆(geschgorin disk estimator,GDE)准则联合多重信号分类(multiple signal classification,MUSIC)算法的变压器局部放电多目标定位方法。首先,利用改进盖氏圆准则确定真实放电源数目;然后,在信源数确定的情况下利用MUSIC算法对多个局部放电源的波达方向进行估计。仿真结果表明,本方法定位精度高,且在白噪声和空间色噪声的情况下仍能对放电源的俯仰角和方位角进行准确估计,能够满足实际工程需求。展开更多
In the digital music landscape, the accuracy and response speed of music recommendation systems (MRS) are crucial for user experience optimization. Traditional MRS often relies on the use of high-performance servers f...In the digital music landscape, the accuracy and response speed of music recommendation systems (MRS) are crucial for user experience optimization. Traditional MRS often relies on the use of high-performance servers for large-scale training to produce recommendation results, which may result in the inability to achieve music recommendation in some areas due to substandard hardware conditions. This study evaluates the adaptability of four popular machine learning algorithms (K-means clustering, fuzzy C-means (FCM) clustering, hierarchical clustering, and self-organizing map (SOM)) on low-computing servers. Our comparative analysis highlights that while K-means and FCM are robust in high-performance settings, they underperform in low-power scenarios where SOM excels, delivering fast and reliable recommendations with minimal computational overhead. This research addresses a gap in the literature by providing a detailed comparative analysis of MRS algorithms, offering practical insights for implementing adaptive MRS in technologically diverse environments. We conclude with strategic recommendations for emerging streaming services in resource-constrained settings, emphasizing the need for scalable solutions that balance cost and performance. This study advocates an adaptive selection of recommendation algorithms to manage operational costs effectively and accommodate growth.展开更多
文摘This paper presents a modified Root-MUSIC algorithm by which the signal DOA estimation performance can be improved when the snapshot number is limited. The operation principlesof this algorithm are described in detail. It is also pointed out theoretically that this is equivalentto have increased the snapshot number and can make the DOA estimation better. Finally, somesimulating results to verify the theoretical analyses are presented.
基金supported by the National Natural Science Foundation of China (10971083, 10801063)the School of Mathematical Sciences Foundation of Jilin University
文摘In this paper, we consider a MUSIC algorithm for locating point-like scatterers contained in a sample on flat substrate. Based on an asymptotic expansion of the scattering amplitude proposed by Ammari et al., the reconstruction problem can be reduced to a calculation of Green function corresponding to the background medium. In addition, we use an explicit formulation of Green function in the MUSIC algorithm to simplify the calculation when the cross-section of sample is a half-disc. Numerical experiments are included to demonstrate the feasibility of this method.
文摘On account of the traditional multiple signal classification(MUSIC)algorithm has poor performance in time delay estimation under the condition of small sampling data and low SNR.In this paper,the traditional MUSIC algorithm is improved.The algorithm combines the idea of spatial smoothing,constructs a new covariance matrix using the covariance information of the measurement data,and constructs a weighted value using the modified noise eigenvalues to weight the traditional estimation spectrum.Simulation results show that the improved algorithm has steeper spectral peaks and better time delay resolution under the condition of inaccurate path number estimation.The time delay estimation accuracy of this algorithm is higher than that of the traditional MUSIC algorithm and the improved SSMUSIC algorithm under the conditions of small sampling data and low SNR.
文摘In this paper,a time-frequency associated multiple signal classification(MUSIC)al-gorithm which is suitable for through-wall detection is proposed.The technology of detecting hu-man targets by through-wall radar can be used to monitor the status and the location information of human targets behind the wall.However,the detection is out of order when classical MUSIC al-gorithm is applied to estimate the direction of arrival.In order to solve the problem,a time-fre-quency associated MUSIC algorithm suitable for through-wall detection and based on S-band stepped frequency continuous wave(SFCW)radar is researched.By associating inverse fast Fouri-er transform(IFFT)algorithm with MUSIC algorithm,the power enhancement of the target sig-nal is completed according to the distance calculation results in the time domain.Then convert the signal to the frequency domain for direction of arrival(DOA)estimation.The simulations of two-dimensional human target detection in free space and the processing of measured data are com-pleted.By comparing the processing results of the two algorithms on the measured data,accuracy of DOA estimation of proposed algorithm is more than 75%,which is 50%higher than classical MUSIC algorithm.It is verified that the distance and angle of human target can be effectively de-tected via proposed algorithm.
文摘This paper gives a MUSIC signal DOA estimation algorithm based on the modified high-order cumulant matrix which is constructed by the recieved data and their conjugate rearrangements. When the snapshot number is limited, this algorithm can improve the signal DOA estimation performances obviously, and its computational complexity scarcely increases. Finally, some simulation results to verify the theoretical analyses are presented.
基金It is supported by the National Natural Science Foundation of China(No.5994 70 0 4)
文摘Multichannel biomagnetometers can be used to measure the spatio temporal magnetic field produced by neural activity in a human brain. The measured data are usually contaminated by noise and some artifact signals. These artifact signals may be caused by heart beats or eye blinks. Actually, these artifact signal sources are also bioelectric activities. In this paper, we demonstrate the effectiveness of MEG MUSIC algorithm for eliminating the artifacts. In the paper, the artifact fields are not considered as noise but as signals that have a linear relationship with their bioelectric source activities. Computer simulations demonstrate that for the localization of sources distributed in the cortical region, the MEG MUSIC algorithm is also efficient under the presence of the artifacts.
文摘准确测量管道介质声速有助于分析介质的密度和组分,而传统的声速测量方法重复性低、鲁棒性差。为了实现介质声速的准确测量,首先,基于管道一维声波理论推导出线阵列传感器在管道轴向位置的声信号模型,介绍了空气与水的理论声速计算公式以及不同管材、管径和壁厚对声速衰减的影响;其次,采用MUSIC(multiple signal classification)波束形成算法将多通道时域数据转换至波数频率域,呈现出斜率与声速相关的“声学脊”;最后,使用DN50不锈钢管道分别在水和空气流量标准装置上进行声速测量实验,与理论数据相比,水中声速的相对误差为1.61%,重复性为0.45%,空气中声速的相对误差为0.59%,重复性为1.27%。结果表明MUSIC算法可准确测量管道一维声波的介质声速。
文摘This article describes the development of an application for generating tonal melodies. The goal of the project is to ascertain our current understanding of tonal music by means of algorithmic music generation. The method followed consists of four stages: 1) selection of music-theoretical insights, 2) translation of these insights into a set of principles, 3) conversion of the principles into a computational model having the form of an algorithm for music generation, 4) testing the “music” generated by the algorithm to evaluate the adequacy of the model. As an example, the method is implemented in Melody Generator, an algorithm for generating tonal melodies. The program has a structure suited for generating, displaying, playing and storing melodies, functions which are all accessible via a dedicated interface. The actual generation of melodies, is based in part on constraints imposed by the tonal context, i.e. by meter and key, the settings of which are controlled by means of parameters on the interface. For another part, it is based upon a set of construction principles including the notion of a hierarchical organization, and the idea that melodies consist of a skeleton that may be elaborated in various ways. After these aspects were implemented as specific sub-algorithms, the device produces simple but well-structured tonal melodies.
文摘实际变压器局部放电定位过程中放电源数目是未知的,常利用传统高分辨波达方向(direction of arrival,DOA)估计算法解决放电定位问题,但在信源数欠估计、过估计情况下存在定位精度低、误差大的问题。为此,本文提出了一种基于改进盖氏圆(geschgorin disk estimator,GDE)准则联合多重信号分类(multiple signal classification,MUSIC)算法的变压器局部放电多目标定位方法。首先,利用改进盖氏圆准则确定真实放电源数目;然后,在信源数确定的情况下利用MUSIC算法对多个局部放电源的波达方向进行估计。仿真结果表明,本方法定位精度高,且在白噪声和空间色噪声的情况下仍能对放电源的俯仰角和方位角进行准确估计,能够满足实际工程需求。
文摘In the digital music landscape, the accuracy and response speed of music recommendation systems (MRS) are crucial for user experience optimization. Traditional MRS often relies on the use of high-performance servers for large-scale training to produce recommendation results, which may result in the inability to achieve music recommendation in some areas due to substandard hardware conditions. This study evaluates the adaptability of four popular machine learning algorithms (K-means clustering, fuzzy C-means (FCM) clustering, hierarchical clustering, and self-organizing map (SOM)) on low-computing servers. Our comparative analysis highlights that while K-means and FCM are robust in high-performance settings, they underperform in low-power scenarios where SOM excels, delivering fast and reliable recommendations with minimal computational overhead. This research addresses a gap in the literature by providing a detailed comparative analysis of MRS algorithms, offering practical insights for implementing adaptive MRS in technologically diverse environments. We conclude with strategic recommendations for emerging streaming services in resource-constrained settings, emphasizing the need for scalable solutions that balance cost and performance. This study advocates an adaptive selection of recommendation algorithms to manage operational costs effectively and accommodate growth.
