共查询到19条相似文献,搜索用时 140 毫秒
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针对在分形噪声1/fα(0≤α2)中检测磁异信号存在的问题,提出了一种自适应噪声抵消器与自适应AR白化滤波器相结合的磁异信号正交基函数(OBF)检测算法——改进的OBF检测算法。由于固定AR白化滤波器对分形噪声1/fα的白化效果不佳,影响了OBF检测算法的性能,因此采用自适应噪声抵消器对被检测信号进行预处理以提高其信噪比,再利用自适应AR白化滤波器对预处理信号进行白化滤波,以实现OBF检测算法的最优化。理论仿真结果表明:当α值接近于0时,改进的OBF检测算法的处理增益略高于未经白化的OBF检测算法;当α值接近于2时,改进的OBF检测算法的处理增益略高于基于AR白化滤波器的OBF检测算法;当α值约等于0.8时,改进的OBF检测算法的处理增益高于其他两种算法7 dB,实验结果表明改进的OBF检测算法可以检测更微弱的磁异信号。 相似文献
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歌曲中的有歌唱部分是音乐的精华所在,也是音乐检索中用户检索的主要部分,传统的歌曲有歌唱部分检测采用的短时固定长度分帧方法没有考虑到音乐信号与一般音频信号的不同,针对于此,文章中提出一种结合音乐信号的节拍特征进行动态分帧的方法,该方法结合乐理知识,首先将音乐信号按照节拍进行分割,在此基础上提取特征,训练分类器,从而检测歌曲中的有歌唱部分,经实验表明,该方法能够对不同风格音乐信号有歌唱部分进行有效的检测,相对传统方法,能够提高检测的精确度. 相似文献
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当一个人随着音乐跺脚或拍手的时候,他就是在进行节拍跟踪。节拍跟踪是理解音乐结构的基础,因此它也是任何试图表现对音乐理解的系统的最重要的能力。该论文提出了一种从音乐信号中提取出节拍的算法。这个算法能够分析出音乐行进的速度以及每一拍出现的时刻,并且能够分辨出其中的强拍与弱拍。这个算法首先采用共振器的方法分析出音乐中最可能存在的两个备选的节拍速度和出现的时刻,然后使用音乐知识最终确定出最可能的节拍,并分辨出其中的强拍与弱拍。 相似文献
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针对帕金森疾病(Parkinson’s Disease,PD)开环深部脑刺激(Deep Brain Stimulation,DBS)疗法存在能耗过多而引起副作用的问题,提出根据患者临床状态变化实时调节刺激参数的自适应闭环DBS方案。选取与临床状态密切相关的内侧苍白球[β]频段(13~35?Hz)振荡功率作为反馈信号,定义随运动状态动态变化的[β]功率值作为参考信号;选取鲁棒性强的模糊控制算法实时求解DBS参数并与传统比例-积分算法的控制效果进行比较;应用皮层-基底核-丘脑网络生理模型验证所设计自适应闭环DBS方案的可行性。将开环130?Hz DBS产生的[β]功率作为期望值时,模糊控制器在成功跟踪期望功率的同时将平均刺激频率降为108.77?Hz,能够降低刺激能耗。在不改变刺激参数的情况下,改变期望的[β]功率值,均能实现成功跟踪,证明了模糊控制器的鲁棒性。设计的基于模糊控制的帕金森状态[β]频段振荡抑制的闭环DBS方案能够根据[β]频段振荡功率变化进行实时跟踪,通过降低开环刺激能耗减少副作用,为临床闭环DBS优化PD疗法提供方案参考。 相似文献
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当利用混沌理论进行微弱信号的检测时,针对不同频率的信号只能分别构建不同的检测系统进行检测,势必使其检测效率低下.本文阐述了一种分频段阈值变换的混沌检测方法,并基于该方法实现了自跟踪扫频检测.为此,首先分析了微弱信号混沌检测方法中的变阈值法和定阈值法,指出了这两种方法的优缺点,然后提出了分频段阈值变换的混沌检测方法,并基于该方法开展了微弱信号的自跟踪扫频检测控制的研究,设计制作了微弱信号自跟踪扫频检测控制电路,并进行了微弱信号自跟踪扫频混沌检测的实验研究.结果表明该检测控制系统可以实现在噪声背景下的中低频率微弱周期信号的自跟踪扫频检测. 相似文献
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针对现有的频谱感知存在信号稀疏度估计所需压缩观测值不能满足信号稀疏度变化时实时跟踪的问题,研究一种基于稀疏系数信息估计的自适应宽带频谱压缩感知方法,在流信号进行稀疏度未知的压缩时,先采集由先验信息得到的观测值数目.在采集到的观测值数目上自适应调整,得到信号稀疏度估计所需的观测值数目,并精确估计信号的稀疏度.仿真结果表明,SCI-CSS算法对流信号频谱能够保持良好的收敛性和较快的跟踪速度,且能有效地确定使信号稀疏度估计所需压缩观测值数目并随信号稀疏度自适应调整,实现对信号稀疏度变化的实时跟踪. 相似文献
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针对计算机智能监控环境,文中提出一种改进的基于像素灰度出现概率最大值的背景建立方法,该方法克服了光照变化对背景重建的影响,使得背景建立的时间大大缩短。并采用一种新的自适应背景更新算法获得背景图像以进行目标检测,这种方法较好地克服了IIR法更新速度难以取值的缺点,使得更新速率可以达到自适应的效果;在目标跟踪阶段,使用基于卡尔曼滤波的方法对检测出的运动目标进行跟踪,由于卡尔曼预测可以大大减小特征匹配的搜索范围,因此提高了跟踪的实时性。实验结果表明,该文的算法能够快速有效地获得、更新背景,并且能够实时地对运动目标进行跟踪。 相似文献
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Matthew E. P. Davies Mark D. Plumbley 《IEEE transactions on audio, speech, and language processing》2007,15(3):1009-1020
We present a simple and efficient method for beat tracking of musical audio. With the aim of replicating the human ability of tapping in time to music, we formulate our approach using a two state model. The first state performs tempo induction and tracks tempo changes, while the second maintains contextual continuity within a single tempo hypothesis. Beat times are recovered by passing the output of an onset detection function through adaptively weighted comb filterbank matrices to separately identify the beat period and alignment. We evaluate our beat tracker both in terms of the accuracy of estimated beat locations and computational complexity. In a direct comparison with existing algorithms, we demonstrate equivalent performance at significantly reduced computational cost 相似文献
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提出了一种基于节拍内音乐谐波特性的乐纹特征提取方法,首先求得每帧音乐的谐波信息,再利用跟踪得到的节拍,计算节拍内所有帧的谐波信息的均值,构成此节拍的乐纹特征矩阵。为了提高音乐检索的效率,设计了一个二级音乐检索算法:根据节拍信息,将与查询音乐片段的每分钟节拍数相近的音乐作为候选音乐,再逐节拍计算所查询音乐的乐纹和候选音乐乐纹的相似度,选择相似度最高的音乐作为检索结果。实验结果表明,提出的乐纹特征和音乐检索算法有效地提高了检索准确率和检索效率。 相似文献
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Automatic mood detection and tracking of music audio signals 总被引:2,自引:0,他引:2
Lie Lu Liu D. Hong-Jiang Zhang 《IEEE transactions on audio, speech, and language processing》2006,14(1):5-18
Music mood describes the inherent emotional expression of a music clip. It is helpful in music understanding, music retrieval, and some other music-related applications. In this paper, a hierarchical framework is presented to automate the task of mood detection from acoustic music data, by following some music psychological theories in western cultures. The hierarchical framework has the advantage of emphasizing the most suitable features in different detection tasks. Three feature sets, including intensity, timbre, and rhythm are extracted to represent the characteristics of a music clip. The intensity feature set is represented by the energy in each subband, the timbre feature set is composed of the spectral shape features and spectral contrast features, and the rhythm feature set indicates three aspects that are closely related with an individual's mood response, including rhythm strength, rhythm regularity, and tempo. Furthermore, since mood is usually changeable in an entire piece of classical music, the approach to mood detection is extended to mood tracking for a music piece, by dividing the music into several independent segments, each of which contains a homogeneous emotional expression. Preliminary evaluations indicate that the proposed algorithms produce satisfactory results. On our testing database composed of 800 representative music clips, the average accuracy of mood detection achieves up to 86.3%. We can also on average recall 84.1% of the mood boundaries from nine testing music pieces. 相似文献
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We present a fuzzy-gain filter for target tracking in a stressful environment where a target may accelerate at nonuniform rates and may also complete sharp turns within a short time period. Furthermore, the target may be missing from successive scans even during the turns, and its positions may be detected erroneously. The proposed tracker incorporates fuzzy logic in a conventional α-β filter by the use of a set of fuzzy if-then rules. Given the error and change of error in the last prediction, these rules are used to determine the magnitude of α and β. The proposed tracker has the advantage that it does not require any assumption of statistical models of process and measurement noise and of target dynamics. Furthermore, it does not need a maneuver detector even when tracking maneuvering targets. The performance of the fuzzy tracker is evaluated using real radar tracking data generated from F-18 and other fighters, collected jointly by the defense departments of Canada and the United States. When compared against that of a conventional tracking algorithm based on a two-stage Kalman filter, its performance is found to be better both in terms of prediction accuracy and the ability to minimize the number of track losses 相似文献
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Erkut Erdem Séverine Dubuisson Isabelle Bloch 《Computer Vision and Image Understanding》2012,116(7):827-841
In this paper, we address the issue of part-based tracking by proposing a new fragments-based tracker. The proposed tracker enhances the recently suggested FragTrack algorithm to employ an adaptive cue integration scheme. This is done by embedding the original tracker into a particle filter framework, associating a reliability value to each fragment that describes a different part of the target object and dynamically adjusting these reliabilities at each frame with respect to the current context. Particularly, the vote of each fragment contributes to the joint tracking result according to its reliability, and this allows us to achieve a better accuracy in handling partial occlusions and pose changes while preserving and even improving the efficiency of the original tracker. In order to demonstrate the performance and the effectiveness of the proposed algorithm we present qualitative and quantitative results on a number of challenging video sequences. 相似文献
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In this paper, we propose a method for robust detection of the vowel onset points (VOPs) from noisy speech. The proposed VOP detection method exploits the spectral energy at formant frequencies of the speech segments present in glottal closure region. In this work, formants are extracted by using group delay function, and glottal closure instants are extracted by using zero frequency filter based method. Performance of the proposed VOP detection method is compared with the existing method, which uses the combination of evidence from excitation source, spectral peaks energy and modulation spectrum. Speech data from TIMIT database and noise samples from NOISEX database are used for analyzing the performance of the VOP detection methods. Significant improvement in the performance of VOP detection is observed by using proposed method compared to existing method. 相似文献