Comparación entre la modulación Wavelet y modulaciones tradicionales

Investigaciones actuales se enfrentan a los desafíos de la creciente demanda de mayor velocidad de datos, mejor calidad de servicio y mayor capacidad de transmisión para ello se ha puesto en marcha la técnica de modulación Wavelet, debido a su robustez ante la interferencia. En este artículo se realizará un análisis comparativo de la tasa de error binario (BER) y la relación señal a ruido (SNR) de las modulaciones Wavelet de las familias; Haar, Daubechies tipo 8 y Coiflets tipo 5 frente a técnicas de modulación tradicionales QPSK y 4-QAM, estos parámetros nos van a permitir saber cuál es la más adecuada para el sistema de comunicación digital , gracias a esto se pudo determinar que las Wavelets que tienen más de 4 momentos de compresión y eliminación de ruido , tales como las de las familias Daubechies tipo 8 y Coiflets tipo 5 presentan un menor margen de error frente a la modulación tradicional 4-QAM lo que no sucede con la modulación QPSK.Current research is facing the challenges of the growing demand for higher data speeds, better quality of service and greater transmission capacity. For this reason, we must implement the Wavelet modulation technique due to the system's robustness against interference. In this article, a comparative analysis of the binary error rate (BER) and the noise ratio (SNR) of the Wavelet modulations of the families will be carried out; Haar, Daubechies type 8 and Coiflets type 5 compared to traditional QPSK and 4-QAM modulation techniques, these parameters will allow us to know which is the most suitable for the digital communication system, thanks to this it was possible to determine that the Wavelets that they have more than 4 moments of compression and noise elimination, such as those of the Daubechies type 8 and Coiflets type 5 families, presenting a lower margin of error compared to traditional 4-QAM modulation, which does not happen with QPSK modulation

The application of non-linear partial differential equations for the removal of noise in audio signal processing

A dissertation submitted in fulfllment for the degree of Masters of Science in the Faculty of Science School of Computer Science and Applied Mathematics October 2017.This work explores a new method of applying partial di erential equations to audio signal processing, particularly that of noise removal. Two methods are explored and compared to the method of noise removal used in the free software Audacity(R). The rst of these methods uses a non-linear variation of the di usion equation in two dimensions, coupled with a non-linear sink/source term, in order to lter the imaginary and real components of an array of overlapping windows of the signal's Fourier transform. The second model is that of a non-linear di usion function applied to the magnitude of the Fourier transform in order to estimate the noise power spectrum to be used in a spectral subtraction noise removal technique. The technique in this work features nite di erence methods to approximate the solutions of each of the models.LG201