Head-Related Transfer Function Modeling Based on Finite-Impulse Response

2013 ◽  
Author(s):  
Jian Zhang ◽  
Risheng Xia ◽  
Chundong Xu ◽  
Junfeng Li ◽  
Yonghong Yan ◽  
...  
Keyword(s):  
Transfer Function ◽  
Impulse Response ◽  
Finite Impulse Response ◽  
Head Related Transfer Function

scholarly journals Projeto de um Estetoscópio Digital para Ausculta Cardíaca

2019 ◽  
Author(s):  
Victor Hugo Ferreira Silva
Keyword(s):  
Transfer Function ◽  
Impulse Response ◽  
Frequency Band ◽  
Fourier Transforms ◽  
Least Squares Method ◽  
Finite Impulse Response ◽  
Gibbs Phenomenon ◽  
Signal Frequency ◽  
Diagnostic Tools ◽  
Low Frequencies

Trying to spread the use of cardiovascular diseases diagnostic tools, this undergraduate thesis had the purpose of creating a digital stethoscope prototype by creating a signal conditioning board composed by filters and amplifiers that emphasize the auscultation frequency band, and by creating a software for the analysis and processing of the cardiac auscultation signal using Matlab tools. The conditioning circuit transfer function modulus (which represents the input and output voltage ratio) was theorically and experimentally estimated. This value has behaved as expected for almost all the auscultation signal frequency band (16 to 1 kHz), just presenting a signal attenuation under the auscultation low frequencies. (16 to 20 Hz). Now the phase response obtained by the transfer function argument (which represents the output and input phase offset) was only theorically estimated but also presented a nonlinear response at low frequencies (16 to 20 Hz). The developed software made use of finite impulse response digital filters implemented by the least squares method to filter the frequencies not present in the auscultation band. Fast Fourier Transforms implemented by the recursive method were also utilized to analyze the signal in the frequency domain. To minimize the Gibbs phenomenon and the spectral leakage Hann windowing functions were utilized. To compensate the delay introduced by the finite impulse response filters the zero-phase filtering technique were utilized. The results had demonstrated that the software frequency response also was satisfactory at high frequencies, differently that at low frequencies. But in contrast, the auscultation samples were successfully filtered on the question of making the heart sounds distinguishable in the phonocardiograms, making possible that the heart rate and sound duration analysis were successfully executed.

FPGA-based Implementation of IIR Filter for Real-Time Noise Reduction in Signal

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Aladin Kapić ◽  
Rijad Sarić ◽  
Slobodan Lubura ◽  
Dejan Jokić
Keyword(s):  
Transfer Function ◽  
Impulse Response ◽  
Discrete Time ◽  
Time Domain ◽  
Digital Filters ◽  
Finite Impulse Response ◽  
Infinite Impulse Response ◽  
Main Role ◽  
Digital Implementation ◽  
Iir Filter

Filtering of unwanted frequencies represents the main aspect of digital signal processing (DSP) in any modern communication system. The main role of the filter is to perform attenuation of certain frequencies and pass only frequencies of interest. In a DSP system, sampled or discrete-time signals are processed by digital filters using different mathematical operations. Digital filters are commonly categorized as Finite Impulse Response (FIR) and Infinite Impulse Response (IIR). This research focuses on the full VHDL implementation of digital second-order lowpass IIR filter for reducing the noisy frequencies on the FPGA board. The initial step is to determine, from continuous time domain function, the transfer function in the complex {s} domain, then map transfer function in complex {z} domain and finally calculate the difference equation in discrete-time domain of the system with adequate coefficients. Prior to the FPGA implementation, the IIR filter is tested in MATLAB using a signal with mixed frequencies and signal with randomly generated noise. The digital implementation is completed by using fixed-point binary vectors and clocked processes.

One Method for Design of Narrowband Lowpass Filters

2003 ◽  
pp. 258-271 ◽  
Author(s):  
Gordana Jovanovic-Dolecek ◽  
Javier Diaz-Carmona
Keyword(s):  
Transfer Function ◽  
Impulse Response ◽  
Finite Impulse Response ◽  
Fir Filter ◽  
Amplitude Change ◽  
Multiple Copies ◽  
Change Function

This chapter describes a design of a narrowband lowpass finite impulse response (FIR) filter using a small number of multipliers per output sample (MPS). The method is based on the use of a frequency-improved recursive running sum (RRS), called the sharpening RRS filter, and the interpolated finite impulse response (IFIR) structure. The filter sharpening technique uses multiple copies of the same filter according to an amplitude change function (ACF), which maps a transfer function before sharpening to a desired form after sharpening. Three ACFs are used in the design, as illustrated in the accompanying examples.

Quantification of the Impact of Uncertainties in Operating Conditions on the Flame Transfer Function With Non-Intrusive Polynomial Chaos Expansion

2018 ◽  
Author(s):  
Alexander Avdonin ◽  
Wolfgang Polifke
Keyword(s):  
Transfer Function ◽  
Impulse Response ◽  
Equivalence Ratio ◽  
Polynomial Chaos ◽  
Finite Impulse Response ◽  
Operating Parameter ◽  
Polynomial Chaos Expansion ◽  
Operating Conditions ◽  
Chaos Expansion ◽  
The Impact

Non-intrusive polynomial chaos expansion (NIPCE) is used to quantify the impact of uncertainties in operating conditions on the flame transfer function of a premixed laminar flame. NIPCE requires only a small number of system evaluations, so it can be applied in cases where a Monte Carlo simulation is unfeasible. We consider three uncertain operating parameters: inlet velocity, burner plate temperature, and equivalence ratio. The flame transfer function (FTF) is identified in terms of the finite impulse response from CFD simulations with broadband velocity excitation. NIPCE yields uncertainties in the FTF due to the uncertain operating conditions. For the chosen uncertain operating bounds, a second-order expansion is found to be sufficient to represent the resulting uncertainties in the FTF with good accuracy. The effect of each operating parameter on the FTF is studied using Sobol indices, i.e. a variance-based measure of sensitivity, which are computed from the NIPCE. It is observed that in the present case uncertainties in the finite impulse response as well as in the phase of the FTF are dominated by the equivalence-ratio uncertainty. For frequencies below 150 Hz, the uncertainty in the gain of the FTF is also attributable to the uncertainty in equivalence-ratio, but for higher frequencies the uncertainties in velocity and temperature dominate. At last, we adopt the polynomial approximation of the output quantity, provided by the NIPCE method, for further UQ studies with modified input uncertainties.

scholarly journals NANO-studio, the design environment of filter banks implemented in standard CMOS technology

2021 ◽  
Author(s):  
Andrzej Handkiewicz ◽  
Mariusz Naumowicz
Keyword(s):  
Impulse Response ◽  
Filter Banks ◽  
Finite Impulse Response ◽  
Infinite Impulse Response ◽  
Cmos Process ◽  
Digital Cmos ◽  
Additional Advantage ◽  
Analysis And Synthesis ◽  
Optimization Parameters ◽  
Synthesis Filter

AbstractThe paper presents a method of optimizing frequency characteristics of filter banks in terms of their implementation in digital CMOS technologies in nanoscale. Usability of such filters is demonstrated by frequency-interleaved (FI) analog-to-digital converters (ADC). An analysis filter present in these converters was designed in switched-current technique. However, due to huge technological pitch of standard digital CMOS process in nanoscale, its characteristics substantially deviate from the required ones. NANO-studio environment presented in the paper allows adjustment, with transistor channel sizes as optimization parameters. The same environment is used at designing a digital synthesis filter, whereas optimization parameters are input and output conductances, gyration transconductances and capacitances of a prototype circuit. Transition between analog s and digital z domains is done by means of bilinear transformation. Assuming a lossless gyrator-capacitor (gC) multiport network as a prototype circuit, both for analysis and synthesis filter banks in FI ADC, is an implementation of the strategy to design filters with low sensitivity to parameter changes. An additional advantage is designing the synthesis filter as stable infinite impulse response (IIR) instead of commonly used finite impulse response (FIR) filters. It provides several dozen-fold saving in the number of applied multipliers.. The analysis and synthesis filters in FI ADC are implemented as filter pairs. An additional example of three-filter bank demonstrates versatility of NANO-studio software.

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