Digital Filters Research Articles

Survey on Power and Area efficient FIR Filter Architecture in Digital Encephalography System

In the process of Electroencephalogram (EEG) acquisition, the electrical signals from the brain are contaminated by numerous noise sources and artifacts. American Clinical Neurophysiology Society recommends digital filtering of acquired EEG signals with an upper cut-off frequency of 70 Hz before display in digital encephalography systems. We propose a linear symmetrical FIR filter architecture for filtering EEG signals using approximate computation techniques. Approximate computation techniques result in lower hardware resources and lower power consumption with some compromise in quality. Software tools used for this study include MATLAB (and its FDA tool) and Xilinx ISE 14.7. The chosen target platform is the Spartan-3e starter FPGA board. We propose the architecture for an Approximate Dadda Tree Multiplier. The proposed approximate multiplier consumes 25% lesser slices and 35.18% lower dynamic power than state-of-the-art approximate multipliers. The proposed FIR filter consumes 19.77% lesser LUTs and 34.97% lower power than state-of-the-art symmetric FIR filter architectures.

Comparing Two Smoothing Approaches in Estimating Kinematic Parameters.

We compare two signal smoothing and differentiation approaches: a frequently used approach in the speech community of digital filtering with approximation of derivatives by finite differences and a spline smoothing approach widely used in other fields of human movement science. In particular, we compare the values of a classic set of kinematic parameters estimated by the two smoothing approaches and assess, via regressions, how well these reconstructed values conform to known laws about relations between the parameters. Substantially smaller regression errors were observed for the spline smoothing than for the filtering approach. This result is in broad agreement with reports from other fields of movement science and underpins the superiority of splines also in the domain of speech.

Fluid face but not gender: Enfacement illusion through digital face filters does not affect gender identity.

It has been shown that observing a face being touched or moving in synchrony with our own face increases self-identification with the former which might alter both cognitive and affective processes. The induction of this phenomenon, termed enfacement illusion, has often relied on laboratory tools that are unavailable to a large audience. However, digital face filters applications are nowadays regularly used and might provide an interesting tool to study similar mechanisms in a wider population. Digital filters are able to render our faces in real time while changing important facial features, for example, rendering them more masculine or feminine according to normative standards. Recent literature using full-body illusions has shown that participants' own gender identity shifts when embodying a different gendered avatar. Here we studied whether participants' filtered faces, observed while moving in synchrony with their own face, may induce an enfacement illusion and if so, modulate their gender identity. We collected data from 35 female and 33 male participants who observed a stereotypically gender mismatched version of themselves either moving synchronously or asynchronously with their own face on a screen. Our findings showed a successful induction of the enfacement illusion in the synchronous condition according to a questionnaire addressing the feelings of ownership, agency and perceived similarity. However, we found no evidence of gender identity being modulated, neither in explicit nor in implicit measures of gender identification. We discuss the distinction between full-body and facial processing and the relevance of studying widely accessible devices that may impact the sense of a bodily self and our cognition, emotion and behaviour.

Digital IIR filters: Effective in edge preservation?

Infinite Impulse Response (IIR) filtering stands as a fundamental technique in various signal processing applications. Despite its widespread use, the scientific community widely acknowledges the suboptimal nature of IIR filters in preserving edges or abrupt transitions in piecewise signals. In situations where meticulous preservation of abrupt signal transitions is crucial, signal processing practitioners often explore alternative methodologies tailored to specific application demands. Consequently, the effectiveness of digital IIR filters in preserving signal edges while filtering out undesirable noise components continues to be a topic of active debate.In response to this limitation (or answering the question posed by the above title), the paper demonstrates that the suboptimal nature of IIR filters in preserving edges arises from the conventional methodology used to compute the output of zero-phase IIR filters. The standard method of output computation equates to solving an unconstrained optimization problem with an ℓ2-norm penalty term. Following this analysis, the paper introduces a refined approach to compute the output of digital IIR filters, aiming to overcome the challenge of preserving abrupt signal transitions. This innovative proposal replaces the ℓ2-norm with an ℓ1-norm, resulting in the development of an IIR filter that dynamically adjusts its coefficients based on the input signal. As a result, this novel approach to output computation effectively preserves essential signal features while simultaneously reducing noise, highlighting the efficacy of digital IIR filters in edge preservation. Therefore, the answer to the aforementioned question greatly depends on the chosen method for computing the output. By employing the suggested approach, the answer is unequivocally yes.

Simplified V/f Control Algorithm for Reduction of Current Fluctuations in Variable-Speed Operation of Induction Motors

This paper introduces a straightforward control strategy aimed at the reduction of current fluctuations within the low-frequency domain of open-loop V/f control in induction motor drives. Traditional control techniques necessitate the addition of a current compensator based on motor parameters and the use of digital filters such as band-pass or high-pass filters. These methods, however, rely on precise motor parameters and involve complex filter design and implementation. The proposed control is capable of suppressing current fluctuations without controlling the slip of the induction motor. The proposed control strategy generates the forced rotation angle and command input voltage using the V/f block and outputs the d-axis voltage using a proportional integral controller to keep the d-axis current constant at zero. The difference between the command input voltage and the d-axis voltage is applied as the q-axis voltage and then applied through SVPWM. In order to verify the effectiveness of the proposed control, the proposed control is implemented and analyzed using power simulation based on the results of the analysis of the causes of current fluctuations in the induction motor. Finally, the effect of suppressing current fluctuations of the induction motor is verified through experimental results. In the 10~19 Hz range, where the conventional V/f control method resulted in current fluctuation rates exceeding 10% and peaking at 113.3% at 13 Hz, the proposed method suppressed the fluctuation rate to below 8.6% across all frequencies. This paper validates the effectiveness of the proposed control strategy through these results.

NEW KIND OF IIR DIGITAL FILTERS INTENDED FOR PULSE PERIOD FILTERING

This paper describes a new kind of infinite impulse response (IIR) digital filter designed for pulse period filtering. The IIR digital filter is designed using a third-order IIR frequency locked loop (IIR FLL), which is based on the time measurement and processing of both, the input and output periods. A general form of the difference equation describing this type of IIR FLL of any order is developed and compared with the corresponding difference equation of classical digital filters. The mathematical analyses in the time domain were performed using the Z transform approach and the theory of linear discrete systems. An analysis of the IIR digital filter was performed in the time and frequency domain. The transfer functions and Z transform of the third-order IIR FLL outputs are developed. The main part of the article is devoted to designing the appropriate IIR FLL digital filter using the corresponding IIR FLL. For this purpose, the theory of IIR digital filter and the corresponding MATLAB tools are used, but taking into account the differences between these systems. The filtering abilities of the designed IIR FLL digital filter are demonstrated. Computer simulation of the designed IIR FLL is made in the time domain to enable precise insight into its properties.

Improved empirical mode decomposition method based on amplitude-frequency characteristic of vortex signals.

The vortex flowmeter occupies a vital position in flow measurement with its unique advantages. It is essentially a fluid vibration instrument, and its measurement process is susceptible to interference, which seriously affects measurement accuracy. In particular, at low flow rates, it is an urgent problem to extract vortex signals from the complex noise. Among many signal processing methods, Empirical Mode Decomposition (EMD) is a time-frequency analysis method suitable for nonlinear, non-stationary signals. EMD can adaptively decompose noisy signals into noise and useful signal components arranged from high frequency to low frequency. For the above problems, an innovative, improved EMD method is proposed in this paper. The digital filter is designed according to the amplitude-frequency characteristic of vortex signals. After filtering, the vortex signal is adjusted to a fixed value, and high-frequency noise is filtered. According to the consistency of the filtered signal's amplitude, we design a decomposition stop criterion for EMD to process the output signal of the vortex sensor. This method not only maintains the characteristic of adaptive decomposition in EMD but also completes the automatic extraction of the vortex signal under complex noise. It provides a new comprehensive method for realizing high-precision and anti-interference vortex flowmeters.

Mirror, Mirror on the Wall, Who Is the Whitest of All? Racial Biases in Social Media Beauty Filters

Digital beauty filters are pervasive in social media platforms. Despite their popularity and relevance in the selfies culture, there is little research on their characteristics and potential biases. In this article, we study the existence of racial biases on the set of aesthetic canons embedded in social media beauty filters, which we refer to as the Beautyverse. First, we provide a historic contextualization of racial biases in beauty practices, followed by an extensive empirical study of racial biases in beauty filters through state-of-the-art face processing algorithms. We show that beauty filters embed Eurocentric or white canons of beauty, not only by brightening the skin color, but also by modifying facial features.

WASA: a low power and high integration readout ASIC for TPCs in 65 nm CMOS

The paper presents the development of a low-power and high-integration readout ASIC (WASA) for time projection chambers (TPCs). Each channel of the ASIC consists of the analog front-end, a waveform sampling ADC and digital signal processing circuits. To reduce power consumption, a simple CR-RC shaper and a digital trapezoid filter are adopted to achieve comparable performance to a CR-RC4 shaper with much lower power. Trigger logic and data buffer have also been integrated to reduce the data bandwidth. A 16-channel prototype chip was fabricated in a 65 nm CMOS process and was tested. The test results were consistent with the simulation. At 40 MSPS sampling rate, the power consumption of the chip was only 4.94 mW per channel, including 1.38 mW from the analog front-end, 0.83 mW from the waveform sampling ADC and 2.73 mW from digital logics. The equivalent noise charge of 569 e+14.8 e/pF has been achieved. The measured dynamic range was 120 fC and the integral nonlinearity was less than 0.74%. More design details and test results will be given in this paper.

On vehicle response under non-Gaussian road profile excitation

Gaussian road profile is widely used to study vehicle response and fatigue damage potential, while field measured road profile often is non-Gaussian. In this paper, a new amplitude modulation method which has full control of cutoff frequency (denoted as Wcut) and amplitude of the amplitude modulation signal is firstly presented to synthesize non-Gaussian road profile with different kurtosis. The forced response of a quarter vehicle under non-Gaussian road profile excitation is then calculated using the ramp invariant digital filter method. The relationship between the vehicle response characteristics and the kurtosis of input non-Gaussian road profile are developed. A case study is used to verify the proposed method. The results show that a small Wcut should be selected so that the high kurtosis of the non-Gaussian road profile is correctly transferred to the vehicle response. The FDS of the vehicle response increases over the entire frequency range as the kurtosis of the input road profile increases.

Concise Historic Overview of Rail Corrugation Studies: From Formation Mechanisms to Detection Methods

Rail corrugation is a serious problem in a railway transportation system, aggravating the operational risk and shortening the lifetime of train–track system. In order to ensure the safety and reliability of the railway system, the detection of rail corrugation is very important. Thus, this study systematically summarizes the recent research progress of rail corrugation. First, this study introduces the definition of rail corrugation and the classification criteria. Then, the formation mechanism of rail corrugation is analyzed in detail, and its adverse consequences are investigated. Further, this study summarizes several main detection methods, which are corrugation-detection methods based on acceleration measurements, wavelet transform methods for corrugation evaluation, computer-vision-based methods for corrugation automatic detection, digital filtering algorithms for rail corrugation detection, and others. In this study, the formation mechanism and detection methods of rail corrugation are systematically described, and various corrugation-detection methods are also introduced in detail. This study not only provides a scientific basis for railway maintenance, but also lays a solid foundation for future experimental design and data analysis. This study can also guide engineering practice to improve the reliability and safety of railway systems. It also provides useful experience for future railway-engineering design and planning, as well as safer and more reliable operation. In general, this study can provide technical support for the detection of rail corrugation to ensure the safety of the rail–track system.

High Spatial Resolution BOTDA Based on Deconvolution and All Phase Digital Filtering

High Spatial Resolution BOTDA Based on Deconvolution and All Phase Digital Filtering

Response spectrum-based analysis of airborne radar random vibration and multi-point control improvement

During the flight of a UAV (unmanned aerial vehicle), the LiDAR device undergoes random vibrations due to the changing flight attitude and wind speed conditions of the UAV. It is important to control the frequency and amplitude of the vibrations within a reasonable range by means of a damping structure. As the vibrations caused by various factors during flight are random and non-linear, this paper innovates the analysis principle and damping control means for the random vibrations of airborne optoelectronic devices. The response spectrum analysis theory is used to establish the shock response spectrum, and an optimised and improved recursive digital filtering method is used to fit the frequencies of random vibration to the synthetic shock response. Considering the uncertainty of the vibration excitation signal, a virtual excitation method is used for the first time to simulate the random vibration to which the radar may be subjected in the air, and to simplify the calculation steps. The shock plate structure is designed using a multi-point control method to innovate a passive response to the random excitation. Finally, a modal analysis of the synthesised impact response was carried out. It is verified that the first six modal frequencies are controlled within 220 Hz, realising the frequency reduction. The amplitude of the three x, y, and z directions is controlled to within 0.5 mm, thus achieving vibration damping.

IR detection module with integrated real-time FIR filter implemented in FPGA

Infrared detectors are usually characterized by 1/f noise when operating with biasing. This type of noise significantly reduces detection capabilities for low-level and slow signals. There are a few methods to reduce the influence of 1/f noise, like filtering or chopper stabilization with lock-in. Using the first one, a simple 1st-order analog low-pass filter built-in amplifier usually cuts off 1/f noise fluctuations at low frequencies. In comparison, the stabilization technique modulates the signal transposing to a higher frequency with no 1/f noise and then demodulates it back (lock-in amplifiers). However, the flexible tuned device, which can work precisely at low frequencies, is especially desirable in some applications, e.g., optical spectroscopy or interferometry. The paper describes a proof-of-concept of an IR detection module with an adjustable digital filter taking advantage of finite impulse response type. It is based on the high-resolution analog-to-digital converter, field-programmable gate array, and digital-to-analog converter. A microcontroller with an implemented user interface ensures control of such a prepared filtering path. The module is a separate component with the possibility of customization and can be used in experiments or applications in which the reduction of noises and unexpected interferences is needed.

On the minimization of multiplier-adders for powers-of-two filter using a novel right to left (R2L) algorithm

The field of digital signal processing has been receiving increasing attention over the years because of its widespread applications in various fields of science, engineering and technology. In connection to this, design of finite impulse response (FIR) filter has drawn enough attention of researchers throughout the globe. A number of promising developments has been carried out over the last few decades which emphasize on the design of hardware efficient filter structure. In this work, one novel Right to Left (R2L) algorithm is proposed which can minimize the number of multiplier-adders for the powers-of-two FIR filter. The requirement of such adders essentially depends upon the number of such non-zero entries and the word-length of the input signal. Comparative study has been performed amongst few such hardware efficient realizations of digital filters. Finally, the proposed approach has been implemented using Xilinx Plan Ahead 14.7 so as to have a clear understanding about the requirement of different hardware blocks on a field programmable device.

Evaluation of High-Frequency Measurement Errors from Turned Surface Topography Data Using Machine Learning Methods.

Manufacturing processes in industry applications are often controlled by the evaluation of surface topography. Topography, in its overall performance, includes form, waviness, and roughness. Methods of measurement of surface roughness can be roughly divided into tactile and contactless techniques. The latter ones are much faster but sensitive to external disturbances from the environment. One type of external source error, while the measurement of surface topography occurs, is a high-frequency noise. This noise originates from the vibration of the measuring system. In this study, the methods for reducing high-frequency errors from the results of contactless roughness measurements of turned surfaces were supported by machine learning methods. This research delves into optimizing filtration methods for surface topography measurements through the application of machine learning models, focusing on enhancing the accuracy of surface roughness assessments. By examining turned surfaces under specific machining conditions and employing a variety of digital filters, the study identifies the Gaussian regression filter and spline filter as the most effective methods at a 22.5 µm cut-off. Utilizing neural networks, support vector machines, and decision trees, the research demonstrates the superior performance of SVMs, achieving remarkable accuracy and sensitivity in predicting optimal filtration methods.

Estimation of the transpulmonary pressure from the central venous pressure in mechanically ventilated patients

Transpulmonary pressure (PL) calculation requires esophageal pressure (PES) as a surrogate of pleural pressure (Ppl), but its calibration is a cumbersome technique. Central venous pressure (CVP) swings may reflect tidal variations in Ppl and could be used instead of PES, but the interpretation of CVP waveforms could be difficult due to superposition of heartbeat-induced pressure changes. Thus, we developed a digital filter able to remove the cardiac noise to obtain a filtered CVP (f-CVP). The aim of the study was to evaluate the accuracy of CVP and filtered CVP swings (ΔCVP and Δf-CVP, respectively) in estimating esophageal respiratory swings (ΔPES) and compare PL calculated with CVP, f-CVP and PES; then we tested the diagnostic accuracy of the f-CVP method to identify unsafe high PL levels, defined as PL>10 cmH2O. Twenty patients with acute respiratory failure (defined as PaO2/FiO2 ratio below 200 mmHg) treated with invasive mechanical ventilation and monitored with an esophageal balloon and central venous catheter were enrolled prospectively. For each patient a recording session at baseline was performed, repeated if a modification in ventilatory settings occurred. PES, CVP and airway pressure during an end-inspiratory and -expiratory pause were simultaneously recorded; CVP, f-CVP and PES waveforms were analyzed off-line and used to calculate transpulmonary pressure (PLCVP, PLf-CVP, PLPES, respectively). Δf-CVP correlated better than ΔCVP with ΔPES (r = 0.8, p = 0.001 vs. r = 0.08, p = 0.73), with a lower bias in Bland Altman analysis in favor of PLf-CVP (mean bias − 0.16, Limits of Agreement (LoA) -1.31, 0.98 cmH2O vs. mean bias − 0.79, LoA − 3.14, 1.55 cmH2O). Both PLf-CVP and PLCVP correlated well with PLPES (r = 0.98, p < 0.001 vs. r = 0.94, p < 0.001), again with a lower bias in Bland Altman analysis in favor of PLf-CVP (0.15, LoA − 0.95, 1.26 cmH2O vs. 0.80, LoA − 1.51, 3.12, cmH2O). PLf-CVP discriminated high PL value with an area under the receiver operating characteristic curve 0.99 (standard deviation, SD, 0.02) (AUC difference = 0.01 [-0.024; 0.05], p = 0.48). In mechanically ventilated patients with acute respiratory failure, the digital filtered CVP estimated ΔPES and PL obtained from digital filtered CVP represented a reliable value of standard PL measured with the esophageal method and could identify patients with non-protective ventilation settings.

A cost-effective approach to measurements of fluorophore temperature sensitivity and temperature change with reasonable accuracy

The demand for measuring fluorophore temperature sensitivity and temperature change in chemical or biological samples has spurred the search for effective methods. While infrared (IR) light-based thermal devices are popular, they are limited to surface temperature measurement. Fluorescence-based thermometry, which utilizes intensity, lifetime, polarization, and spectrum change, provides the temperature information directly from the samples and can have high temporal and spatial resolution. However, measuring fluorescence can be tricky and expensive. A cost-effective approach to achieving reasonable accuracy is highly desired. This study introduces such an approach, employing a light-emitting diode (LED) for fluorophore excitation and a laser diode (LD) for sample heating, with a phone camera recording fluorescence changes. A data processing method converts the video into digital data, processed through digital filters. Utilizing a small-volume cuvette enhances heating efficiency. This study serves as a practical guide for inexperienced individuals, including students, instructors, and researchers, facilitating entry into the field and navigating the complexities of fluorescence-based thermometry.

Quantized information-theoretic learning based Laguerre functional linked neural networks for nonlinear active noise control

Traditional functional linked neural networks (FLNNs) impose a significant computational burden due to their input expansion, primarily stemming from the utilization of digital filters. This paper presents a Laguerre FLNNs filter for nonlinear active noise control (NANC) systems. By employing the truncated Laguerre series, the presented filter achieves effective approximation of long primary paths with a reduced filter length. Moreover, we develop adaptive algorithms rooted in information-theoretic learning (ITL) within the framework of the Laguerre-FLNNs NANC model. Using the ITL criterions, a Laguerre filtered-s maximum correntropy criterion (LFsMCC) algorithm is derived and a Laguerre filtered-s quantized minimum error entropy criterion (LFsQMEE) algorithm is proposed by minimizing Renyi’s quadratic entropy. To reduce the computation cost, an online vector quantization method is utilized to improve the LFsQMEE. This technique selectively quantizes the error vectors, reducing them to a smaller subset of samples within the codebook. Moreover, an enhanced LFsQMEE with a fiducial point is introduced. The steady-state performance and the computational complexity are analyzed. Theoretical analysis is validated through simulations and the control performance of the proposed model and algorithms is tested in experiments with both simulated and real paths.

Estimation of phase distortions of the photoplethysmographic signal in digital IIR filtering

Pre-processing of the photoplethysmography (PPG) signal plays an important role in the analysis of the pulse wave signal. The task of pre-processing is to remove noise from the PPG signal, as well as to transmit the signal without any distortions for further analysis. The integrity of the pulse waveform is essential since many cardiovascular parameters are calculated from it using morphological analysis. Digital filters with infinite impulse response (IIR) are widely used in the processing of PPG signals. However, such filters tend to change the pulse waveform. The aim of this work is to quantify the PPG signal distortions that occur during IIR filtering in order to select a most suitable filter and its parameters. To do this, we collected raw finger PPG signals from 20 healthy volunteers and processed them by 5 main digital IIR filters (Butterworth, Bessel, Elliptic, Chebyshev type I and type II) with varying parameters. The upper cutoff frequency varied from 2 to 10 Hz and the filter order—from 2nd to 6th. To assess distortions of the pulse waveform, we used the following indices: skewness signal quality index (SSQI), reflection index (RI) and ejection time compensated (ETc). It was found that a decrease in the upper cutoff frequency leads to damping of the dicrotic notch and a phase shift of the pulse wave signal. The minimal distortions of a PPG signal are observed when using Butterworth, Bessel and Elliptic filters of the 2nd order. Therefore, we can recommend these filters for use in applications aimed at morphological analysis of finger PPG waveforms of healthy subjects.