Digital Filters Research Articles

Stream analysis for a sub-catchment of Red River (Vietnam) using isotopic technique and recursive digital filter method

River streams, in general, comprise of two flows: quick flow and baseflow. The baseflow is closely related to geological catchment properties, and understanding the baseflow contribution to stream flow is very important in the planning of water resources management. The baseflow in a sub-catchment of the Red River in Vietnam was quantified using the isotopic technique, and results were compared with Eckhardt’s recursive digital filter (RDF) method. Results of the isotopic approach showed that groundwater is recharged from regions at 300 to 800 m above mean sea level. The upstream baseflow gains from Holocene and Pleistocene aquifers throughout the year, contributing to 65 ± 4 % of the river discharge. On the contrary, the midstream baseflow contributes 44.6 ± 6.5 % of the river’s annual discharge to both Holocene and Pleistocene aquifers. The downstream is more complicated, where the baseflow loses to the Pleistocene aquifer and gains 73 ± 17 % of the river's annual discharge from the Holocene aquifer. The loss of baseflow was attributed to the high rate of groundwater mining.Maintaining the vegetative cover over the recharge areas is recommended to reduce runoff and increase groundwater potential so that the baseflow could sustain the river stream.

Editorial for JEC Volume 2 Issue 2 (2023)

This editorial presents innovative research at the intersection of edge computing and various disciplines, demonstrating the transformative potential of edge computing technologies. The issue includes a study on a digital Proportional-Integral-Derivative (PID) regulator model for controlling unmanned aerial vehicles, using digital filtering methods and a genetic algorithm; discusses an autonomous Internet of Things (IoT) system for monitoring classroom microclimates, contributing to the understanding of how microclimate parameters influence the physiological state of students; details the design and implementation of an educational model for a smart home, integrating various subsystems and renewable energy sources. This issue aims to inspire further exploration and innovation in edge computing, driving the field forward and opening up new possibilities for technology and society.

Serial Analog-Digital QAM Modems Based on Complex Band-Pass Filters with LF Butterworth Prototypes

The article is devoted to the development and implementation of quadrature amplitude modulation algorithms based on an analog complex band-pass filter with Butterworth low-frequency prototypes. The use of complex Butterworth band pass filters makes it possible to obtain carrier signals with practically non-overlapping spectra. But the analog complex Butterworth filter has a non-linear phase-frequency response and, accordingly, the impulse responses of which are infinite and asymmetric. An overview of the development and implementation of a serial QAM modem based on an analog Butterworth complex band-pass filter and an inverse digital FIR filter. The procedure for obtaining the expression for the impulse response of analog complex band-pass Butterworth filters is considered. With the help of circuit simulation, the frequency response and impulse response of such a filter are determined. The choice of the center frequency is carried out by setting two coefficients. A block diagram of a serial data transmission system with quadrature amplitude modulation based on an analog complex Butterworth bandpass filter and an inverse digital FIR filter is proposed. The results of its circuit simulation in the Micro-Cap environment are presented.

High-Speed Wavelet Image Processing Using the Winograd Method with Downsampling

Wavelets are actively used to solve a wide range of image processing problems in various fields of science and technology. Modern image processing systems cannot keep up with the rapid growth in digital visual information. Various approaches are used to reduce the computational complexity and increase computational speeds. The Winograd method (WM) is one of the most promising. However, this method is used to obtain sequential values. Its use for wavelet image processing requires expanding the calculation methodology to cases of downsampling. This paper proposes a new approach to reduce the computational complexity of wavelet image processing based on the WM with decimation. Calculations have been carried out and formulas have been derived that implement digital filtering using the WM with downsampling. The derived formulas can be used for 1D filtering with an arbitrary downsampling stride. Hardware modeling of wavelet image filtering on an FPGA showed that the WM reduces the computational time by up to 66%, with increases in the hardware costs and power consumption of 95% and 344%, respectively, compared to the direct method. A promising direction for further research is the implementation of the developed approach on ASIC and the use of modular computing for more efficient parallelization of calculations and an even greater increase in the device speed.

Topography measurement methods evaluation for entire bending-fatigued fracture surfaces of specimens obtained by explosive welding

In this paper, the methods of compensation of differences in the results of entire bending-fatigued fracture surface topographies were presented. The roughness evaluation was performed with a focus variation microscope and confocal surface topography measurement techniques. The differences in the ISO 25178 roughness parameters were investigated and procedures for their compensation were studied. It was found that various types of optical measurements can cause differences in the errors occurring in the measurement process, such as outliers, and noise. The reduction of differences in the various optical roughness measurements can be attained when measurement errors are compensated. For this study, the applications of general procedures available in commercial software can be suitable for improvements of the roughness measurement results, such as raw data thresholding technique, digital filtering (S-filter), power spectral density, and autocorrelation function analyses. The validation of measurement techniques was proposed for areal and profile studies, including analysis of differences in the calculation areal ISO 25178 roughness parameters.

A Frequency-Weighting Digital Filter in Sound Level Meter Based on Neural Computing Method

Frequency weighting networks are a critical component of a sound level meter (SLM), and their error characteristics directly determine the performances of SLM. For reducing the high-frequency error of the [Formula: see text] frequency-weighting filters with the bilinear transformation method (BTM), a design method for [Formula: see text] frequency-weighting filters based on neural computing method (NCM) is proposed. A detailed algorithm for solving the filter coefficients is provided, and the amplitude-frequency characteristics of the [Formula: see text] frequency-weighting filters with BTM and NCM are compared in detail. The experimental results show that the amplitude-frequency characteristics of the [Formula: see text] frequency-weighting filters in SLM with NCM are significantly better than those of BTM. The filter meets the requirements of the first class SLM defined by IEC61672, which demonstrates the effectiveness of this proposed method.

Analysis of improved digital filter inflow generation methods for compressible turbulent boundary layers

We propose several enhancements to improve the accuracy and performance of the digital filter turbulent inflow generation technique and assess their efficacy in the context of wall-resolved large-eddy simulations of a compressible turbulent boundary layer. Improvements of accuracy include a more realistic correlation function for the transversal directions, target length scales that vary with wall-distance, and a counter-intuitive approach that involves the suppression of streamwise velocity fluctuations at the inflow. For improving the computational performance, we propose to generate the inflow data in parallel in single precision and at a prescribed time interval based on the turbulence time scale, and not at every time-step of the simulation. Based on the results of 7 wall-resolved large-eddy simulations, we find that the new correlation functions and the considered performance improvements are beneficial and therefore desired. Suppressing streamwise velocity fluctuations at the inflow leads to the fastest relaxation of the pressure fluctuations; however, this approach increases the adaptation length defined in terms of compliance with the von Kármán integral equation. The adaptation length can be shortened by artificially increasing the wall-normal Reynolds stresses, thereby preserving the desired turbulence kinetic energy level. A detailed inspection of the Reynolds stress transport budgets reveals that the observed spurious spatial transients are largely driven by pressure-related terms. For instance, increased values of u′p′¯ are found throughout the computational domain when a physical Reynolds stress distribution is prescribed at the inflow. Therefore, efforts to enhance digital filter techniques should aim at modeling pressure fluctuations as well as their correlation with the velocity components.

ASIC implementation of ECG denoising FIR filter by using hybrid Vedic–Wallace tree multiplier

AbstractThe design of hand‐held portable devices for cardiovascular health monitoring based on the analysis of electrocardiogram (ECG) is a hot topic of research nowadays. Digital filters, possibly designed using digital multipliers, are a critical module in the design of such analysis systems. This paper presents the ASIC design of a 64th‐order digital low‐pass FIR filter to be used in ECG denoising applications. The FIR filter is optimized for usage in battery‐operated portable systems, wherein power consumption and on‐chip area are crucial parameters of concern. These challenges are met by employing a novel multiplier architecture, which we design by hybridizing the two popular digital multiplication algorithms, namely, the Vedic multiplication algorithm and the Wallace tree multiplication algorithm. The proposed multiplier consumes lower area and power consumption than either of the aforementioned conventional multiplication algorithms. This is established through FPGA‐based implementations on Artix‐7 FPGA, for the various wordlengths. The area and power optimizations are further exercised by two proposed techniques, namely, elimination of redundant multipliers, and power gating using the proposed zero‐detector circuit. RTL‐to‐GDSII flow has been completed using Cadence digital design and sign‐off tools for SCL 180 nm technology. The results indicate that the proposed filter architecture occupies 16.38% lower area and 79.58% lower power consumption than the contemporary designs described in the literature.

Practical Considerations for Implementing Adaptive Acoustic Noise Cancellation in Commercial Earbuds

Active noise cancellation has become a prominent feature in contemporary in-ear personal audio devices. However, due to constraints related to component arrangement, power consumption, and manufacturing costs, most commercial products utilize fixed-type controller systems as the basis for their active noise control algorithms. These systems offer robust performance and a straightforward structure, which is achievable with cost-effective digital signal processors. Nonetheless, a major drawback of fixed-type controllers is their inability to adapt to changes in acoustic transfer paths, such as variations in earpiece fitting conditions. Therefore, adaptive-type active noise control systems that employ adaptive digital filters are considered as the alternative. To address the increasing system complexity, design concepts and implementation strategies are discussed with respect to actual hardware limitations. To illustrate these considerations, a case study showcasing the implementation of a filtered-x least mean square-based active noise control algorithm is presented. A commercial evaluation board accommodating a low-cost, fixed-point digital signal processor is used to simplify operation and provide programming access. The earbuds are obtained from a commercial product designed for noise cancellation. This study underscores the importance of addressing hardware constraints when implementing adaptive active noise cancellation, providing valuable insights for real-world applications.

A 0.99-pJ/b 10-Gb/s Receiver With Fast Recovery From Sleep Mode Under Voltage Drift

This brief presents a 10 Gb/s receiver for an application processor (AP)-to-timing controller-embedded display (TED) interface that is capable of recovering its operating frequency fast from the sleep mode under the supply voltage drift. A hybrid clock and data recovery (CDR) loop is employed to support the fast entering and exiting of the sleep mode by adding AND gates to the digital loop filter, while offering good jitter performance by utilizing an analog loop filter. Also supply voltage drift cancellation (SVDC) circuit is added to maintain constant current in the presence of supply voltage drift. Thanks to the hybrid CDR and SVDC, even if the supply voltage drift occurs during the sleep mode, the same frequency is recovered fast without frequency re-tracking. A prototype chip fabricated in 28-nm CMOS technology occupies an active area of 0.089mm2 with 0.99-pJ/bit energy efficiency in the active mode. The measured results show that the frequency is recovered within 36 ns even if the worst-case supply voltage drift occurs during the sleep mode.

Characterization of Single Event Effect in a Radiation Hardened Programmable Read-Only Memory in a 130 nm Bulk CMOS Technology

The concept of memory that can only be read but cannot be changed seems strange at first. In reality, it is found that it has great application potential, such as the processor with a fixed purpose, the initial set value of the microprocessor BIOS, and these data are stored in Programmable Read-Only Memory (PROM) to quickly realize system functions. The PROM storage content is fixed, greatly simplifying his design. The radiation of space particles is the main factor causing the failure of the electronic system of spacecraft. The PROM storage array of the space electronic system is the most basic guarantee for the normal operation of the electronic system. The chip adopts domestic 130 nm standard technology of Complementary Metal Oxide Semiconductor (CMOS), Muller-C digital filter is used in the peripheral subsystem of PROM storage array, and the core cell uses Dual Interlocked Cell (DICE) and ring gate and other radiation hardening technologies to design a 32Kx8bit radiation resistant asynchronous programmable PROM. Pre-silicon of devices was verified by Technology Computer Aided Design (TCAD), and post silicon radiation verification was completed through radiation experiment. The post silicon radiation experiment showed that the total ionizing Dose (TID) capacity of the PROM chip was ≥100 Krad (Si), the critical value of single event upset (SEU) was ≥37.1 MeV·cm2/mg, the critical value of single event latch up was ≥98 MeV·cm2/mg, meeting the life requirements of the initial value storage of aerospace electronic systems. These performances ensure the reliable operation of the space electronic system after restart.

A High-Bandwidth Current Estimator With Self Tunning for Digital Buck Controller

In order to solve the low-cost problem of high-speed current sampling in digital buck controllers, a current estimation method based on the direct current resistance (DCR) current detection principle is proposed in this paper. The inductor current including direct current (DC) and alternating current (AC) is obtained by performing high-frequency digital filtering on the voltage across the inductor ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V_L</i> ). Quantitative analysis of various factors affecting the accuracy of current estimation is carried out. For improving the estimated current accuracy, the multi-phase interleaved clock sampling technique and the algorithm of the average duty cycle in the filter cycle are proposed to improve the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V_L</i> accuracy in each filter cycle. Meanwhile, considering the completeness of the current estimation algorithm, a calibration mechanism with a known current sink to adjust filter parameters online is adopted for the change of the inductance ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> ) and its equivalent impedance ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R_L</i> ) due to process and aging. The proposed algorithm is verified in a buck prototyping board. Experimental results are presented to show that the proposed method is effective in both fixed frequency and variable frequency control modes. The DC and AC accuracy of estimated current reach 5% and 2%, respectively. The estimated inductor current delay is within 100 ns.

Efficient model of PID controller of unmanned aerial vehicle

The modern stage of science and technology development is distinguished by the widespread use of digital signal processing. The use of digital processing for effective control of aircraft and other technical equipment remains relevant for many industries. The paper considers the problem of building a model of a digital PID-regulator, which can be used in unmanned aerial vehicles. It is proposed to base the regulator on the methods of digital filtering (realisation of the differential component using a digital filter with a finite impulse response). Calculation of digital filter coefficients is performed using genetic algorithm. This approach allows to increase the accuracy of the model, to provide the calculation of PID-regulator coefficients using classical PID-regulator methods. The software on Python programming language realizing the proposed method has been developed. The effectiveness of the developed model is demonstrated in simulation.

Study of a High-Precision Read-Out Integrated Circuit for Bridge Sensors.

Bridge sensors are widely used in military and civilian fields, and their demand gradually increases each year. Digital sensors are widely used in the military and civilian fields. High-precision and low-power analog-to-digital converters (ADCs) as sensor read-out circuits are a research hotspot. Sigma-delta ADC circuits based on switched-capacitor topology have the advantages of high signal-to-noise ratio (SNR), good linearity, and better compatibility with CMOS processes. In this work, a fourth-order feed-forward sigma-delta modulator and a digital decimation filter are designed and implemented with a correlated double sampling technique (CDS) to suppress pre-integrator low-frequency noise. This work used an active pre-compensator circuit for deep phase compensation to improve the system's stability in the sigma-delta modulator. The modulator's local feedback factor is designed to be adjustable off-chip to eliminate the effect of process errors. A three-stage cascade structure was chosen for the post-stage digital filter, significantly reducing the number of operations and the required memory cells in the digital circuit. Finally, the layout design and engineering circuit were fabricated by a standard 0.35 μm CMOS process from Shanghai Hua Hong with a chip area of 9 mm2. At a 5 V voltage supply and sampling frequency of 6.144 MHz, the modulator power consumption is 13 mW, the maximum input signal amplitude is -3 dBFs, the 1 Hz dynamic range is about 118 dB, the modulator signal-to-noise ratio can reach 110.5 dB when the signal bandwidth is 24 kHz, the practical bit is about 18.05 bits, and the harmonic distortion is about -113 dB, which meets the design requirements. The output bit stream is 24 bits.

Feature-Based Bearing Fault Classification Using Taylor–Fourier Transform

This paper proposes a feature-based methodology for early bearing fault detection and classification in induction motors through current signals using the digital Taylor–Fourier transform (DTFT) and statistical methods. The DTFT allows the application of narrow bandwidth digital filters located in the spurious current signal components, wherewith it is possible to gain information to detect bearing issues and classify them using statistical methods. The methodology was implemented in MATLAB using the digital Taylor–Fourier transform for three fault types (bearing ball damage, outer-race damage, and corrosion damage) at different powering conditions: power grid source at 60 Hz and adjustable speed drive applied (60 Hz, 50 Hz, 40 Hz, 30 Hz, 20 Hz, and 10 Hz) in loading and unloading conditions. Results demonstrate a classification accuracy between 93–99% for bearing ball damage, 91–99% for outer-race damage, and 94–99% for corrosion damage.

Influence of noise masking on leak pinpointing: Experimental analysis on a laboratory test rig for leak noise correlation.

The efficient management of water distribution networks requires the detection and mitigation of leaks that result in significant water losses, economic costs, and potential health hazards. This experimental study focuses on the optimal frequency range for accurately locating a water leak in a distribution network using the noise correlation approach while mitigating the influence of background noise associated with water consumption from users. Through laboratory experimental tests, a digital bandpass filter was defined in order to pre-process signals and to improve cross-correlation analysis within the pertinent frequency range. This was done by characterising the frequency content of leak-induced noise, noise masking resulting from water consumption, and background noise. The analysed signals were recorded using hydrophones installed within the pipes of a laboratory test rig under different conditions of water flow rate. The spectra analysis assessed the influence of varying water flow rates on the acoustic sound field within the pipeline system. Additionally, the results of the analysis made it possible to discriminate clearly between noise generated by leaks and noise attributed to water consumption. This distinction is useful for implementing suitable filters, and also to establish a threshold ratio of leak flow rate to water consumption flow rate for effective pre-filtering. This study aims to establish a methodological framework that can effectively differentiate between acoustic signals stemming from leaks and noise generated by other sources within the system, to improve leak location accuracy through the noise correlation approach.

Research on ADS-B spoof detection technology based on radio spectrum features

Abstract This paper discusses and analyzes the 1090ES mode ADS-B and examines the airborne ADS-B transponder and ground monitoring sensing nodes. The ADS-B signal receiver structure converts the received radio signal to a zero IF signal for digital filtering to obtain phase information. The cognitive radio spectrum monitoring technology mainly uses periodic characteristic monitoring to maximize the network's security in the era of artificial intelligence. For a set of ADS-B messages from the same source, the correlation coefficients of the two variation amounts are carried out to discriminate between real targets and spoofed interference, and the source consistency detection method is used to reduce the probability of false alarms. The results show that when the number of signal bars is greater than 11, the correlation value of the real signal is greater than 0.61, while the correlation value of the spoofed signal is around 0.22, which can be better distinguished.

Discrete-time state delayed systems with saturation arithmetic: overflow oscillation-free realization

ABSTRACT In many smart systems, such as cloud computing, networked control, manufacturing, and telecommunication, the effects of time delays are unavoidable. Saturation nonlinearity is common in many smart systems (e.g. electric systems with limited actuator power supplies, mechanical systems with position and speed constraints, fixed-point digital filters, etc.). Therefore, the study of stability of discrete-time systems (DTSs) with time delay and saturation is of high importance in practice. The global asymptotic stability (GAS) problem of such systems is investigated in this paper. The saturation nonlinearity is constrained by a convex hull with a free matrix whose infinity norm is smaller than or equal to unity. A new Lyapunov-based GAS criterion for DTSs with time-varying delay and state saturation is established. The GAS problem for DTSs with constant delay and saturation is also discussed. The obtained results can be used to ensure the absence of overflow oscillations in the considered system. In comparison to several existing criteria, the approach yields improved stability results. An example is provided to demonstrate the importance of the presented results.

An algorithm for the design of optimal finite wordlength FIR filters

In practical FIR digital filter applications it is often necessary to represent the filter coefficients with a finite number of bits. The finite wordlength coefficient restriction reduces the filter quality and increases the filter deviation. This increase can be reduced substantially if the optimal finite wordlength coefficients are used. Computing these coefficients is more difficult and can be slow. It was shown before that the computation time can be significantly reduced with the help of a lower bound on the deviation increase. Derivation of a new algorithm that uses a much better lower bound is the purpose of this paper. We consider the general case of a length N filter with a discrete set of allowable real coefficients and demonstrate the effectiveness of the new algorithm on a set of filter design cases. The results show that this algorithm reduces the computation times up to 3 times when compared with the previously best results.

Evaluation of Neutron Cross-Section Data Using Gaussian Mixture Model and Digital Filter

For the accurate estimation of neutron cross-section data, evaluation of nuclear data is mandatory to fulfill the need of nuclear science and technology. In this work, the evaluation of 232Th(n,2n)231Th, 241Am(n,2n)240Am, 100Mo(n,2n)99Mo, and 96Mo(n,p)96Nb reaction cross-section data is carried out using a novel method. This novel method of evaluation employs a cluster-based piecewise evaluation followed by a digital filter for merging the evaluated curves. The clusters in the experimental data and model data are identified using the probabilistic method of the Gaussian Mixture Model. The clustered experimental data are then regressed using the polynomial regression technique. The model data are generated using the Talys 1.9 code, and the model deficiency due to the complex random nature of nuclear reactions is also accounted here using chi-squared analysis. Evaluation in each cluster is then carried out independently using the popular Kalman filter technique. For obtaining a single smooth evaluated curve for the whole energy range, the popular smoothing digital filter, the Savitzky-Golay Filter, is employed for the first time in nuclear data evaluation. The proposed evaluated curves and existing evaluated curves of 232Th(n,2n)231Th, 241Am(n,2n)240Am, 100Mo(n,2n)99Mo, and 96Mo(n,p)96Nb reactions from nuclear data libraries such as ENDF/BVIII.0, JEFF-3.3, JENDL-4.0, CENDL-3.1, and TENDL 2021 are compared and found to be in good agreement. It is also found that generally, evaluation methods are data dependent, and so, a single evaluation method may not be applicable for all reactions of all nuclides. Since piecewise evaluation is cluster dependent, selecting the appropriate cluster makes this method robust for almost all reactions of all nuclides. Also, it is proven that this novel method of evaluation is a promising method demonstrating the potential of this approach for evaluation based on the chi-squared goodness-of-fit test with respect to standard evaluated library ENDF/BVIII.0 and experimental data.