In this paper, a fuzzy method is proposed to estimate kernel density function online. To achieve this goal, Gaussian mixture model is generated by the fuzzy algorithm. Defuzzifier operator is modified to make it suitable for this application. Means and variances of the model are adapted using observed data in each new sample. Then, rule weights are tuned by minimising the expected L ₂ risk function of the estimated and true PDFs. In contrast to the existing approaches, our approach does not require fine-tuning parameters for a specific application, specific forms of the target distributions are not assumed, and temporal constraints are not considered on the observed data. The algorithm is simple and easy to use. Simulation results show the capability of the proposed algorithm in online and accurate estimation of kernel density function.

In this paper, the authors address the tasks of audio source counting and separation for two-channel instantaneous mixtures. This goal is achieved in two steps. First, a novel scheme is proposed for estimating the number of sources and the corresponding channel intensity difference (CID) values. For this purpose, an angular spectrum is evaluated as a function of the ratio of the magnitude spectrogram of the two channels and the peak locations of that spectrum are obtained. In the second stage, a new approach is developed for extracting the individual source signals exploiting a Bayesian non-parametric modelling. The mean field variational Bayesian approach is applied for inferring the unknown parameters. Classification is then performed on the inferred active CID values to obtain the individual source magnitude spectrograms. This way, the number of spectral components used for modelling each source is found automatically from the data. The Bayesian approach is compared with the standard Kullback–Leibler non-negative tensor factorisation method to illustrate the effectiveness of Bayesian modelling. The performance of the source separation is measured by obtaining the existing metrics for multichannel blind source separation evaluation. The experiments are performed on instantaneous mixtures from the dev2 database.

The authors previously proposed an improved multiband-structured subband adaptive filter (IMSAF) algorithm. In this contribution, they first present two delayless structures of the IMSAF algorithm to remove delay in the signal path. Then, they study the transient and steady-state behaviour of the IMSAF algorithms based on the energy conservation arguments and paraunitary condition imposed on the analysis and synthesis filter banks. The analysis does not require a model for the input signal. Simulation results show that the proposed delayless IMSAF algorithm has a faster convergence rate than the traditional delayless subband adaptive filtering algorithms. Theoretical analysis of the IMSAF algorithm is in good agreement with computer simulation results.

The authors made an analysis on computational complexity of block least mean square (BLMS) finite impulse response (FIR) filter and decompose the filter computation into M sub-filters, where M = N/L, N is the filter length and L is the block-size. The proposed decomposition scheme favours time-multiplexing the filtering computation and weight-increment term computation of BLMS algorithm. Using the proposed scheme, they have derived an efficient architecture for BLMS FIR filter. The proposed structure can be reconfigured for different filter lengths with negligible overhead complexity and it supports variable convergence factor. Besides, the proposed structure has 100% hardware utilisation efficiency and its register complexity is independent of block-size. Compared with recently proposed LMS-based FIR structure the proposed structure involves L times more multipliers, proportionately less adders and the same number of registers, and it offers L times higher throughput. Application specific integrated circuit (ASIC) synthesis results show that the proposed structure for block-size 4 and filter-length 64 involve 21.4% less area-delay product (ADP) and 26.6% less energy per sample (EPS) than those of the existing structure and offers 3.8 times higher throughput.

Two efficient techniques are proposed in this study for the multiple pitch estimation of polyphonic music. The partial magnitude rearrangement separates the overlapped partials into their possible pitches. The harmonic error can be corrected by harmonic relation confirmation. Random combinations of up to six notes at different pitches are analysed statically within one frame over the samples from 21 pitched instruments. The accuracy, efficiency, and robustness of the method using these two techniques are verified by three groups of experiments. The results show that the proposed techniques achieve a better balance between the higher accuracy and the lower computation cost.

This paper proposes a fast and precise adaptive filtering algorithm for online estimation under a non-negativity constraint. A novel variable step-size (VSS) non-negative normalised least-mean-square (NLMS)-type algorithm based on the mean-square deviation (MSD) analysis with a non-negativity constraint is derived. The NLMS-type algorithm under the non-negativity constraint is derived by using the gradient descent of the given cost function and the fixed-point iteration method. Furthermore, the VSS derived by minimising the MSD yields improvement of the filter performance in the aspects of the convergence rate and the steady-state estimation error. Simulation results show that the proposed algorithm outperforms existing algorithms.

With the increasing use of high data rate navigation signals, the detection performance is severely affected by sign transition. An acquisition method based on multiple correlation strategies fusion (MCSF) has been proposed to reduce the correlation loss caused by the sign transition. The detection performances of non-coherent (NCH) method, zero-padding (ZP) method and MCSF in the presence of sign transition have been analysed. The theoretical and simulation results show that the proposed method can provide 1–3 dB acquisition sensitivity improvement compared with the NCH and ZP methods, and reduce the mean acquisition time by 21.3 and 8.5%, respectively. Moreover, the real data from GPS L5 and BeiDou Navigation Satellite System B2I have been used to analyse the performance.