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This paper presents the steps one needs to take in order to run a signal processing algorithm designed in Simulink on the ARM processor of smartphones. The steps are conveyed by transitioning two signal processing application examples from Simulink to smartphone. The application examples involve background noise classification and lane departure detection. Considering that Simulink programming is...
Cochlear implant patients often complain about their difficulty in understanding speech in noisy environments. Currently a fixed noise suppression algorithm is used in cochlear implants regardless of the characteristics of the speech or noise environment. Access to an intelligent mechanism to determine the noise environment on-the-fly in order to automatically switch between different noise suppression...
This paper presents an integrated speech enhancement (SE) method for the noisy MRI environment. We show that the performance of SE system improves considerably when the speech signal dominated by MRI acoustic noise at very low SNR is enhanced in two successive stages using two-channel SE methods followed by a single-channel post processing SE algorithm. Actual MRI noisy speech data are used in our...
Performance of two Adaptive (nLMS and Normalized Sign-error LMS) and a single channel (LogMMSE) speech enhancement algorithms are tested on a floating point DSP to reveal their effectiveness in enhancing speech corrupted in noisy MRI environment with very low SNR. The purpose of experiments is to reduce the fatigue of the listener by eliminating the strong MRI noise. The experiments use actual data...
Conventional adaptive active noise control (ANC) methods aim to attenuate the acoustic noise over the frequency band of interest indiscriminately using the sound pressure level (SPL) measurement (or the measurement of the residual error variance). However, SPL does not correctly reflect the human perception of attenuated noise due to the frequency selective sensitivity of human hearing system. A-weighting...
Periodic signals (since they can be easily predicted) can be canceled much more effectively when compared to non- periodic/stochastic signals. A large class of acoustic noise sources have an underlying periodic process that generates a periodic noise component, and thus the acoustic noise can in general be modeled as the sum of a periodic signal and a random signal (usually a background noise). In...
A new iterative algorithm for separating mixtures of multi-channel signals is proposed. This algorithm extends the instantaneous independent component analysis algorithm to multi-channel blind source separation algorithm. Separation is processed by decomposing convolutive mixtures to instantaneous mixtures. Simulation results for real fMRI (functional magnetic resonance imaging) scanner noise show...
A novel integrated photonic architecture is introduced and used to realize an optical filter with direct form I realization. The architecture offers gain from semiconductor optical amplifiers, and this gain results in an active optical filter whose filter response depends on the individual gains. The presence of gain provides advantages in filter performance, and tunable and adaptive functionality...
We present application of adaptive LMS-based method using two different sub-band filtering techniques for active reduction of 3T-fMRI acoustic noise. Analysis and design of the sub-band filters are discussed based on the characteristics of the noise. Using the fMRI-brain scanner acoustic noise, performance of the methods are analyzed and compared for different number of sub-band filters
The development of improved control theories has been an on-going activity, and several truly outstanding control methodologies have been developed. Meanwhile, modern integrated circuit technology has produced the Digital Signal Processor (DSP), which offers substantial computational power at readily affordable prices. These parallel developments offer an unprecedented opportunity for practical...
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