Luiz F. Q. Silveira

Classification System of Pathological Voices Using Correntropy

This paper proposes the use of a similarity measure based on information theory called correntropy for the automatic classification of pathological voices. By using correntropy, it is possible to obtain descriptors that aggregate distinct spectral characteristics for healthy and pathological voices. Experiments using computational simulation demonstrate that such descriptors are very efficient in the characterization of vocal dysfunctions, leading to a success rate of 97% in the classification. With this new architecture, the classification process of vocal pathologies becomes much more simple and efficient.

Analysis and optimization of wavelet-coded communication systems

Since its advent, wavelet coding has been recognized as a promising technique for wireless transmission systems, especially due to its low decoding complexity and good performance over multipath fading. However, this technique requires unusual modulation schemes in order to be fully exploited. A BER analysis of wavelet-coded transmission systems over Rayleigh fading channels is presented in this work. This analysis is used in the design of novel signal constellations for wavelet-coded systems by means of numerical performance optimization. Numerical results obtained from analysis and simulations show that the wavelet-coded systems derived herein have very good performance characteristics over fading channels.

Performance evaluation of the correntropy coefficient in automatic modulation classification

Abstract Automatic modulation classification (AMC) techniques have applications in a variety of wireless communication scenarios, such as adaptive systems, cognitive radio, and surveillance systems. However, a common requirement to most of the AMC techniques proposed in the literature is the use of signal preprocessing modules, which can increase the computational cost and decrease the scalability of the AMC strategy. This work proposes the direct use of a similarity measure based on information theory for the automatic recognition of digital modulations, which is known as correntropy coefficient. The performance of correntropy in AMC applied to channels subject to additive white Gaussian noise (AWGN) is evaluated. Specifically, the influence of the kernel size on the classifier performance is analyzed, since it is the only free parameter in correntropy. Besides, a relationship between its respective value and the signal-to-noise ratio (SNR) of the channel is also proposed. Considering the investigated modulation techniques, numerical results obtained by simulation demonstrate that there are high accuracy rates in classification, even at low SNR values. By using correntropy, AMC task becomes simpler and more efficient.

Performance of a PSK system with wavelet time diversity over flat Rayleigh fading channels

This paper presents a novel system for transmission over wireless channels. This system combines a smart interleaving that uses a Wavelet Coefficient Matrix (WCM) with a time diversity scheme. It is shown by computational simulation that the proposed system presents a good performance over channels with memory characterized by the flat Rayleigh fading.

Cyclostationary correntropy: Definition and applications

Abstract Information extraction is a frequent and relevant problem in digital signal processing. In the past few years, different methods have been utilized for the parameterization of signals and the achievement of efficient descriptors. When the signals possess statistical cyclostationary properties, the Cyclic Autocorrelation Function (CAF) and the Spectral Cyclic Density (SCD) can be used to extract second-order cyclostationary information. However,second-order statistics tightly depends on the assumption of gaussianity, as the cyclostationary analysis in this case should comprise higher-order statistical information. This paper proposes a new mathematical formulation for the higher-order cyclostationary analysis based on the correntropy function. The cyclostationary analysis is revisited focusing on the information theory, while the Cyclic Correntropy Function (CCF) and Cyclic Correntropy Spectral Density (CCSD) are also presented. The CCF has different properties compared with CAF that can be very useful in non-gaussian signal processing, especially in the impulsive noise environment which implies in the expansion of the class of problems addressed by the second-order cyclostationary analysis. In particular, we prove that the CCF contains information regarding second- and higher-order cyclostationary moments, being a generalization of the CAF. The performance of the aforementioned functions in the extraction of higher-order cyclostationary characteristics is analyzed in a wireless communication system in which non-gaussian noise is present. The results demonstrate the advantages of the proposed method over the second-order cyclostationary.

Optimal processor dynamic-energy reduction for parallel workloads on heterogeneous multi-core architectures

With the increase in the number of cores in processor chips observed in recent years, design choices-such as the number of cores in chip, the amount of resources per core, and whether to design homogeneous or heterogeneous chips-need to be given proper support. Several studies on heterogeneous multi-core processors are concerned with performance improvements. In this work, we propose mathematical models to analyze some of these design issues with focus on the reduction of processor dynamic energy. In particular, these models allow the comparison of the dynamic-energy consumption of multi-core architectures when they execute a workload in the same amount of time while allowing different core operating frequency between the compared architectures. The results of the analysis allow chip designers to choose the right conditions for optimal energy savings in heterogeneous multi-core chips based on the parallel fraction of the workloads and on the distributions of the resources among the cores in the chip. Under a simplified context, the devised models agree with the consolidated knowledge that heterogeneous multi-core chips have considerable advantage over homogeneous multi-core and single-core architectures in terms of energy efficiency.

Fuzzy Wavelet Neural Network Using a Correntropy Criterion for Nonlinear System Identification

Recent researches have demonstrated that the Fuzzy Wavelet Neural Networks (FWNNs) are an efficient tool to identify nonlinear systems. In these structures, features related to fuzzy logic, wavelet functions, and neural networks are combined in an architecture similar to the Adaptive Neurofuzzy Inference Systems (ANFIS). In practical applications, the experimental data set used in the identification task often contains unknown noise and outliers, which decrease the FWNN model reliability. In order to reduce the negative effects of these erroneous measurements, this work proposes the direct use of a similarity measure based on information theory in the FWNN learning procedure. The Mean Squared Error (MSE) cost function is replaced by the Maximum Correntropy Criterion (MCC) in the traditional error backpropagation (BP) algorithm. The input-output maps of a real nonlinear system studied in this work are identified from an experimental data set corrupted by different outliers rates and additive white Gaussian noise. The results demonstrate the advantages of the proposed cost function using the MCC as compared to the MSE. This work also investigates the influence of the kernel size on the performance of the MCC in the BP algorithm, since it is the only free parameter of correntropy.

Video Synchronization With Bit-Rate Signals and Correntropy Function

We propose an approach for the synchronization of video streams using correntropy. Essentially, the time offset is calculated on the basis of the instantaneous transfer rates of the video streams that are extracted in the form of a univariate signal known as variable bit-rate (VBR). The state-of-the-art approach uses a window segmentation strategy that is based on consensual zero-mean normalized cross-correlation (ZNCC). This strategy has an elevated computational complexity, making its application to synchronizing online data streaming difficult. Hence, our proposal uses a different window strategy that, together with the correntropy function, allows the synchronization to be performed for online applications. This provides equivalent synchronization scores with a rapid offset determination as the streams come into the system. The efficiency of our approach has been verified through experiments that demonstrate its viability with values that are as precise as those obtained by ZNCC. The proposed approach scored 81% in time reference classification against the equivalent 81% of the state-of-the-art approach, requiring much less computational power.

Low-complexity receiver for wavelet-filtered M-ary modulations over flat-fading channels

As originally designed, the wavelet coding technique efficiently overcomes the fading effects, but limits the spectral efficiency of these systems to 1 bit/s/Hz. Furthermore, the coded symbols are modulated by unusual signal constellations that need to be designed by optimization methods. An alternative approach based on wavelet matrix to increases the communication system robustness to time-varying fading is proposed in another work by the same authors. This can be easily adapted to any wireless communication system maintaining its original spectral efficiency. However the derivation of receiving strategies is more critical under this novel wavelet-matrix based systems. This paper presents a receiving strategies which is show to be simple and effective, giving rise to outstanding performance gains over conventional amplitude/phase modulations with the same spectral efficiency.

Iterative decoding for serial concatenation with wavelet encoding

An iterative decoder for serial concatenations that have a wavelet encoder as the inner encoder is evaluated in this paper. In particular, a new approach for soft-input soft- output wavelet decoder is proposed, which consider an optimal soft demapping scheme recently proposed for wavelet-coded communication systems. Preliminary results of performance evaluation are presented, where a concatenation with a convolutional encoder over a flat fading Rayleigh channel is investigated. These results show the effectiveness of the proposed decoding technique and suggest that its is potentially useful as a new means to increase the performance benefits produced by wavelet coding in flat fading conditions over wireless channels.