René Fabián Vázquez-Bautista

Hybrid Voltage‐Multipliers Based Switching Power Converters

Abstract. This work presents a derivation of PWM DC-DC hybrid converters by combining traditional converters with the Cockcroft–Walton voltage multiplier, the voltage multiplier of each converter is driven with the same transistor of the basic topology; this fact makes the structure of the new converters very simple and provides high-voltage gain. The traditional topologies discussed are the boost, buck-boost, Cuk and SEPIC. They main features of the discussed family are: (i) high-voltage gain without using extreme duty cycles or transformers, which allow high switching frequency and (ii) low voltage stress in switching devices, along with modular structures, and more output levels can be added without modifying the main circuit, which is highly desirable in some applications such as renewable energy generation systems. It is shown how a multiplier converter can become a generalized topology and how some of the traditional converters and several state-of-the-art converters can be derived from the generalized topologies and vice-versa. All the discussed converters were simulated, additionally experimental results are provided with an interleaved multiplier converter.

Enhancing Biomedical Images Using the UFIR Filters with Recursive Responses

In this paper we present a novel computational scheme to determine the impulse response of the UFIR filters. A recursive form of impulse response is developed using the theory of the discrete orthogonal polynomials. An example of an enhanced of medical image is considered to compare its performance versus the matrix formulation of the impulse response UFIR filters. Finally, some quantitative and qualitative evaluations are carried out to verify its efficiency based on RMSE analysis.

Optimal detection of multiplicative watermarks in Laplacian channels

In this work, we propose a model for an optimal detector of digital watermarks for Laplacian channels, the watermark embedding algorithm is the multiplicative embedding rule in time domain, the optimal detection equation and the threshold equation are derived using maximum likelihood (ML) and Neyman-Pearson criterion. The resulting system is blind and has very low complexity. Computer simulations are carried out applying the proposed model to audio signals and results prove that the proposed system is able to detect watermarks even if the watermarked object was severely attacked by noise, low pass filtering among other attacks.

Enhancing ultrasound images using the recursive p-step unbiased FIR filter

In this paper, we present a computational scheme for the implementation of p-step UFIR filter ultrasound image processing. The recursive scheme is focused both signal to noise ratio and root mean-square-error on filter improved performance. In this way, quantitative evaluations are computed to verify the performance carried out by the new recursive computational scheme under metrics. On the other hand, qualitative evaluations are showed for both cases: signals (one dimensional) and images (two dimensional). Finally, this efficient computational algorithm manifests an outstanding signal/image enhancing with strong metric convergence despite the computational complexity.

An analysis of key points of p-lag median hybrid FIR Filters in applications to image processing

In this paper we give an analysis of special points of the noise power gain of p-lag median hybrid FIR filters in applications to image processing. An important feature of the p-lag gain is that, at some cross points, it converges to the reduced degree one. The results are evaluated in terms of the signal-to-noise ratio (SNR) and root mean square error (RMSE) metrics. We show that image enhancing with different degree FIR filters at special lags allows getting best results depending on applications.

Adaptive algorithm-based fused Bayesian maximum entropy-variational analysis methods for enhanced radar imaging

In this paper we address an adaptive computational algorithm to improve the Bayesian maximum entropy-variational analysis (BMEVA) performance for high resolution radar imaging and denoising. Furthermore, the variational analysis (VA) approach is aggregated by imposing the metrics structures in the corresponding signal spaces. Then, the formalism for combining the Bayesian maximum entropy strategy with the VA paradigm is presented. Finally, the image enhancement and denoising benefits produced by the proposed Adaptive Bayesian maximum entropy-variational analysis (ABMEVA) method are showed via simulations with real-world radar scene

Integer Wavelet Transform Based Watermarking System for PCM Signals

In this paper, a watermarking system based on the integer wavelet transform is proposed. A set of different wavelets was chosen for this propose so their performance as watermark transmission channel can be analyzed. The watermark is embedded in the second decomposition level of the wavelet transform of a PCM signal in a block wise approach, the coefficients of the wavelet transform are assumed to be accurately modeled as a Laplacian channel. A set of attacks were performed in order to test system’s robustness, we found that this approach is robust against several attacks such as additive white noise, low pass filtering, cropping, among other attacks; the best suited wavelet class for developing watermarking systems was identified too.

Semi Fragile Watermarking System in Temporal Domain for PCM Audio Signals

In this work, a watermark detection system for audio signals in temporal domain is proposed, the watermark embedding algorithm is the multiplicative embedding rule and the optimal detection equation is derived for this constraints using the maximum likelihood (ML) criterion. The optimal threshold equation is also derived using the Neyman-Person criterion and the resulting system is blind and has very low complexity. Computer simulations were performed applying the proposed model to audio signals and results show that the proposed system is semi fragile since it is able to detect watermarks if the watermarked object was severely attacked by noise, low pass filtering among other attacks but is not capable of detecting watermarks for others attacks such MP3 compression.