Direction of arrival estimation has many applications in communications. Though MUSIC and ESPRIT are by far the mostly studied algorithms, there have been growing interests in cyclostationarity based algorithms for their higher selectivity. In addition to carrier frequency and baud rate, OFDM signals show cyclostationarity caused by the cyclic prefix. In this paper we have studied the direction...

Separation of music signals is an interesting but difficult problem. It is helpful for many other music researches such as audio content analysis. In this paper, a new music signal separation method is proposed, which is based on harmonic structure modeling. The main idea of harmonic structure modeling is that the harmonic structure of a music signal is stable, so a music signal can be represen...

With the explosive growth of music recordings, automatic classification of music emotion becomes one of the hot spots on research and engineering. Typical music emotion classification (MEC) approaches apply machine learning methods to train a classifier based on audio features. In addition to audio features, the MIDI and lyrics features of music also contain useful semantic information for pred...

We propose a new catalog-based speech-music separation method for background music removal. Assuming that we know a catalog of the background music, we develop a generative model for the superposed speech and music spectrograms. We represent the speech spectrogram by a Non-negative Matrix Factorization (NMF) model and the music spectrogram by a conditional Poisson Mixture Model (PMM). By choosi...

Separation of music signals is an interesting but difficult problem. It is helpful for many other music researches such as audio content analysis. In this paper, a new music signal separation method is proposed, which is based on harmonic structure modeling. The main idea of harmonic structure modeling is that the harmonic structure of a music signal is stable, so a music signal can be represen...

In this paper we consider the problem of error localization of complex DFT codes and the reconstruction of message. A propagator-based subspace algorithm is proposed for error localization of quantized DFT codes. The propagator method requires only linear operations and does not require any eigendecomposition of syndrome covariance matrix as in conventional subspace method such as MUSIC etc. Th...

This paper presents a simple algorithm that efficiently discovers and extracts repeating patterns in music. The algorithm can detect not only exact repeating patterns, but also partial and approximate patterns. The method is based on the time distance of two interval pairs that are similar and uses the accumulation of the distance for evidence of repeating patterns. Users can recognize repeatin...

6.1 Spectral Estimation Methods 6.1.1 Bartlett Method 6.2 Minimum Variance Distortionless Response Estimator 6.3 Linear Prediction Method 6.4 Maximum Entropy Method 6.5 Maximum Likelihood Method 6.6 Eigenstructure Methods 6.7 MUSIC Algorithm 6.7.1 Spectral MUSIC 6.7.2 Root-MUSIC 6.7.3 Constrained MUSIC 6.7.4 Beam Space MUSIC 6.8 Minimum Norm Method 6.9 CLOSEST Method 6.10 ESPRIT Method 6.11 Wei...

6.1 Spectral Estimation Methods 6.1.1 Bartlett Method 6.2 Minimum Variance Distortionless Response Estimator 6.3 Linear Prediction Method 6.4 Maximum Entropy Method 6.5 Maximum Likelihood Method 6.6 Eigenstructure Methods 6.7 MUSIC Algorithm 6.7.1 Spectral MUSIC 6.7.2 Root-MUSIC 6.7.3 Constrained MUSIC 6.7.4 Beam Space MUSIC 6.8 Minimum Norm Method 6.9 CLOSEST Method 6.10 ESPRIT Method 6.11 Wei...