Implementation Of Filter Research Articles

Design and Implementation of Least Mean Square Adaptive Filter Using Verilog

Adaptive filters are ability of adaptation to an unknown environment. These filters have been used widely because of its capable of operating in an unknown system and low power implementation of hardware. Adaptive filters have great range of signal processing and control operations for the tracking time variations of input statistics and Robust to the noise immunity. These filters used various Areas like Noise cancelling (interface cancelling), system identification, inverse modelling and echo predication. Adaptive filters structures have the adaptive algorithms to perform the time variations of the input statics and Robust to the noise cancelling. The most popular algorithm is LMS (Least Mean Square) it produces the least mean square of error signal in the adaptive filter to minimize noise power. Adaptive filter structures follow the two algorithms RLS and LMS. RLS algorithms excellent performance with increased complexity and the filter coefficients that minimize waited linear least squares cost function relating to the input signals. It requires infinite memory for error signal. LMS algorithms are simplest to understand and describe the hardware of the system compare to the RLS (Recursive Least Square). LMS algorithms are follows the stochastic gradient descent method to minimize the error signal and de-nosing task. It estimates the gradient vector from the input data and LMS incorporates an iterative procedure that makes successive corrections to the weight vector in the direction of the negative of the gradient vector which leads to minimum mean square error. It doesn’t require correlation functions for calculations. The main aim of the project is to design the LMS algorithm based adaptive filter using Verilog HDL to reduce the power consumption, hardware complexity and improving the noise cancelling for the adaptive filter on the FGPA boards. An important challenge in the LMS adaptive filters design implementation of structural model in the Verilog HDL for image processing to target the noise cancelling, power and hardware complexity. Tool use for implementation the structural model of LMS filter is vivado tool and Xilinx software for FPGA board implementation.

A Practical Study to Enhance Pressure Signal Quality in Mechanical Ventilators Using Moving Average Filtration: A Comparative Study

Undesirable noise and interference present a substantial obstacle in the process of obtaining biomedical signals for analysis and diagnosis. It is necessary to reduce the noise and enhance signal quality for many designs of medical devices such as Mechanical Ventilators (MV), patient monitors and overall biosignal processing. To contribute for addressing this problem, and for medical applications such as MV which are used for critical diseases such as pneumonia, COVID 19 etc. This paper, conducted comparative study to evaluate the performance of a 3-point Moving Average Filter (MAF) and a 5-point MAF in order to reducing noise and improving signal quality in MVs which are used in medical applications. MATLAB was utilized to perform filter approximation, realization and analysis. LabVIEW was employed for pressure signal data acquisition, implementation, and Signal-to-Noise Ratio (SNR) calculation. Experimental data, which needed for filters implementation, were obtained by running a MV connected to an artificial lung and a reference device which is used to measure pressure signal. In general, 3 point presented better SNR against 5 points MAF for pressure signal required in MVs. This approach can potentially enhance healthcare quality by providing better quality of biomedical signals which are used in medical devices.

Mail Encryption using ChaCha20

—Email communication plays a vital role in modern society, facilitating both personal and professional interactions. However, ensuring the security and confidentiality of sensitive information exchanged via email remains a significant concern. This project presents the development and implementation of an email filter utilizing the ChaCha20 encryption algorithm. ChaCha20 is a symmetric stream cipher algorithm designed by Daniel J. Bernstein. It's often used in encryption protocols and applications, particularly in the context of securing internet traffic. It's known for its speed and security, and it's part of the TLS (Transport Layer Security) protocol suite, among other applications. ChaCha20 operates on 64-byte blocks and uses a key size of 256 bits. It's considered to be quite secure and has seen widespread adoption in various security-sensitive applications. Before encryption can occur, a cryptographic key needs to be generated. For ChaCha20, a secure random key is typically generated. The key should be kept secret and shared only between the sender and the intended recipient(s). For maximum security, ChaCha20 encryption in email is often implemented as part of an end-to-end encryption scheme. This means that the content of the email is encrypted on the sender's device and can only be decrypted by the intended recipient, with no intermediary (including email service providers) having access to the plaintext. Overall, ChaCha20 plays a crucial role in ensuring the confidentiality of email communication by encrypting the content of messages, thereby protecting it from unauthorized access or interception.

Enhancing Vehicle Location Prediction Accuracy with Road-Aware Rectification for Multi-Access Edge Computing Applications

In future 6G networks, real-time and accurate vehicular data are key requirements for enhancing the data-driven multi-access edge computing (MEC) applications. Existing estimation techniques to forecast vehicle position aim to meet the real-time data needs but compromise accuracy due to a lack of context awareness. While algorithms such as the Kalman filter improve estimation accuracy by considering certainty-grading and current-state estimate of measurements, they do not include the road context, which is vital for more accurate predictions. Unfortunately, current implementations of linear Kalman filters are not road-aware and struggle to predict a two-dimensional movement accurately. To this end, we propose a significant road-aware rectification-assisted prediction mechanism that enhances the modified Kalman filter predictions by incorporating road awareness. The parameters used for the Kalman filter include vehicle location, angle, speed, and time. In contrast, road-aware location rectification incorporates predicted location and lane shape, increasing the accuracy and precision of vehicle location predictions, reaching up to 99.9%. Performance is evaluated by comparing actual, predicted, and rectified vehicular traces at different speeds. The results demonstrate that the prediction error is approximately 0.005, while the proposed rectification process further reduces the error to 0.001, highlighting the effectiveness of the proposed approach. Overall, results support the idea of provisioning accurate, proactive, and real-time vehicular location data at the edge using a road-aware approach, thereby revolutionizing 6G vehicle location provisioning in MEC.

Digital three-stage recursive-separable image processing filter with variable sizes of scanning multielement aperture

Objectives. The main aim of digital image processing is to increase clarity while maintaining image quality and eliminate noise. However, the amount of information contained in digital image files is growing year after year. This circumstance negatively affects processing time, critical for systems with high load requirements on the computing platform. In this regard, the use of digital filters which enable a reduction to the processing time of incoming data is important. In order to resolve this issue, adaptive filters with different sizes of multielement processing aperture are being developed to improve image clarity and preserve image details. Filters with adaptive properties are able to change their parameters during data processing, and provide maximum performance as the aperture size increases. The aim of the work is to develop a type of recursively separable digital filter with variable sizes of a scanning multielement aperture which allows the number of computational operations to be reduced while maintaining the efficiency of filtering input data (images).Methods. The work used recursive-separable methods and algorithms to construct digital filters.Results. An algorithm for the recursive-separable implementation of a digital filter is described, and the final view of the processing aperture and its three-dimensional appearance are presented. In order to evaluate the performance of the filter, a comparison of the developed algorithm with the classical two-dimensional convolution algorithm was carried out. The experiment was performed using images of various sizes and consisted of determining the time spent on the process of processing the test image. The study established that the processing time of a test image using the developed filter is on average 5 times less than the time taken by the classical two-dimensional convolution algorithm. The optimal coefficients for magnifying the central element and raising the positive part of the aperture of a digital filter were determined, enabling the efficiency of its use to be enabled.Conclusions. The studies show the effectiveness of using the developed recursive-separable two-dimensional filter to improve image clarity and reduce the time spent on processing.

Feasibility study of modularized pin ridge filter implementation in proton FLASH planning for liver stereotactic ablative body radiotherapy

Objective.We previously developed a FLASH planning framework for streamlined pin-ridge-filter (pin-RF) design, demonstrating its feasibility for single-energy proton FLASH planning. In this study, we refined the pin-RF design for easy assembly using reusable modules, focusing on its application in liver stereotactic ablative body radiotherapy (SABR).Approach.This framework generates an intermediate intensity-modulated proton therapy (IMPT) plan and translates it into step widths and thicknesses of pin-RFs for a single-energy FLASH plan. Parameters like energy spacing, monitor unit limit, and spot quantity were adjusted during IMPT planning, resulting in pin-RFs assembled using predefined modules with widths from 1 to 6 mm, each with a water-equivalent-thickness of 5 mm. This approach was validated on three liver SABR cases. FLASH doses, quantified using the FLASH effectiveness model at 1-5 Gy thresholds, were compared to conventional IMPT (IMPT-CONV) doses to assess clinical benefits.Main results.The highest demand for 6 mm width modules, moderate for 2-4 mm, and minimal for 1- and 5-mm modules were shown across all cases. At lower dose thresholds, the two-beam case reduced indicators including liverV21Gyand skinDmaxby >19.4%, while the three-beam cases showed reductions⩽11.4%, indicating the need for higher fractional beam doses for an enhanced FLASH effect. Positive clinical benefits were seen only in the two-beam case at the 5 Gy threshold. At the 1 Gy threshold, the two-beam FLASH plan outperformed the IMPT-CONV plan, reducing dose indicators for all relevant normal tissues by up to 31.2%. In contrast, the three-beam cases showed negative clinical benefits, with skinDmaxand liverV21Gyincreasing by up to 17.4% due to lower fractional beam doses and closer beam arrangements.Significance.This study evaluated the feasibility of modularizing streamlined pin-RFs in single-energy proton FLASH planning for liver SABR, offering guidance on optimal module composition and strategies to enhance FLASH planning.

Enhancing Chashma Barrage water level estimations with sentinel 3 radar altimetry

Satellite Radar altimetry has emerged as a powerful tool for monitoring inland water bodies including rivers, lakes, and coastal regions. However, challenges persist regarding its accuracy, particularly over complex terrains. This study addresses these challenges by enhancing water level estimation accuracy in complex environments. Although the scope of our study may appear limited in terms of temporal and spatial scales, it aims to contribute additional validation results for a comprehensive water-level database utilizing satellite radar altimetry data. In this paper, we applied two pulse filter criteria on Sentinel-3A radar data—Pulse Peakiness (PP) and Misfit (Mf)—to enhance the selection of altimetry waveforms. After applying the filters, the estimated water levels show improved accuracy when validated against in-situ observations. Pulses from non-water surfaces were excluded using riverbank boundaries to ensure higher-quality pulses. A total of six scenarios were considered where the PP and Mf criteria were used to optimize water level estimates. The results indicate that Mf < 1.5 performs well (RMSE = 0.27 m, R = 0.93), and PP > 0.3 yields even better outcomes (RMSE = 0.28 m, R = 0.95). These findings underscore the significance and efficacy of filtering in enhancing the accuracy of water level estimation. The dataset correlation (R) increased substantially, from 0.088 to 0.935–0.953, with the implementation of filters. Additionally, the RMSE significantly improved, reducing from 4.2 m to 0.26–0.27 m with filter parameters. As anticipated, filters removed data points but vastly improved results. Integrating multi-mission satellite data can compensate for data loss and augment overall quantity and quality.

High-pass filters do not consistently strengthen associations between acoustic indices and avian species richness

High-pass sound filters are a common form of audio manipulation that attenuates or removes low frequency sounds from audio recordings. While high-pass filters are used to reduce anthropogenic noise, there is limited guidance on their optimal application and their effects on acoustic indices—numerical values derived from passive acoustic monitoring (PAM) recordings to summarize acoustic information. Here, we investigated the effects of three high-pass filter treatments (482 Hz, 1 kHz, and 2 kHz) on eight commonly implemented acoustic indices and one less-commonly used convolutional neural network metric. Specifically, we used simulated soundscapes with three levels of traffic noise interference and then applied the filter treatments to field recordings collected throughout Illinois, USA during May 2022–July 2023 and derived acoustic indices to further understand these effects. Our analysis revealed that interactions between acoustic filtering and vehicular noise pollution have diverse effects on the nine acoustic indices, both in simulated soundscapes and empirical PAM recordings. In general, a 1 kHz or 2 kHz filter was necessary in order to produce significant changes in acoustic index values. However, none of the applied filtering treatments consistently strengthened correlations between the examined acoustic indices and avian species richness. The Acoustic Complexity Index (ACI), Acoustic Richness Index (AR), and CityBioNet (CB) demonstrated greater resistance to biologically non-informative changes caused by filter implementation, with CB showing a notably higher correlation with species richness compared to the other examined indices. Our findings suggest that ACI, AR, and CB may be better suited to studies of avian species richness in soundscapes with high levels of anthropogenic noise. Future research is needed to establish best practices for acoustic filtering, understand the behavior of acoustic indices under various environmental contexts, and explore alternative methodologies for avian monitoring in human-modified contexts.

Fast Implementation of Image Preprocessing for SAR Scene Matching Guidance

Abstract The design of SAR scene matching guidance scheme and the hardware allocation of algorithm module are discussed in this paper. Aiming at the requirement of SAR image preprocessing module, a fast robust feature extraction preprocessing method based on FPGA is designed, and the fast implementation of Gabor filter and wavelet transform is completed. Through the hardware-in-the-loop simulation module test and experimental verification, the FPGA-based pre-processing fast implementation is about 60 times shorter than the DSP processing time, and the results of FPGA, DSP and digital simulation in the hardware-in-the-loop simulation process are consistent. The proposed method not only shortens the processing time of scene matching guidance system, but also ensures the accuracy of SAR image matching.

Complementary Metal Oxide Semiconductor Circuit Realization of Inverse Chebyshev Low-Pass Filter of Order (1 + α)

This paper presents the CMOS circuit realization of a low-pass Inverse Chebyshev fractional-order filter (FOF) of order (1 + α) using the inverse-follow-the-leader feedback (IFLF) topology. A nonlinear least squares optimization routine is used to determine the coefficients of the fractional-order transfer function to approximate the stop-band characteristics. The Inverse Chebyshev FOF of orders 1.3, 1.6, and 1.9 using cross-coupled operational transconductance amplifier (OTA) was designed in united microelectronics corporation (UMC) 180 nm complementary metal–oxide–semiconductor process. The MATLAB and Cadence Spectre simulations are used to validate the implementation of the fractional-order filter of orders 1.3, 1.6 and 1.9. The dynamic range (DR) of the filter is found to be 83.04 dB, 86.13 dB, and 84.71 dB, respectively, for order of 1.3, 1.6, and 1.9. The simulation results such as magnitude response, transient plot, Monte Carlo, and PVT plots, have justified the design accuracy.

Optimization of Frequency Stability in Hydraulic Load Frequency Control Systems Using Controllers with Filters

This study meticulously investigates the design and analysis of a Load Frequency Control (LFC) system tailored explicitly for hydraulic power systems by employing diverse configurations of PID controllers, namely Proportional (P), Proportional-Integral (PI), Proportional-Derivative (PD), Proportional-Integral-Derivative (PID), Proportional-Derivative-Fractional (PDF), and Proportional-Integral-Derivative-Fractional (PIDF). The primary objective of this exploration is to improve frequency stability in response to various load fluctuations typical in hydraulic systems. A comprehensive evaluation of each controller's performance is conducted through extensive MATLAB simulations, focusing on critical performance metrics such as rise time, peak time, steady-state time, and maximum overshoot. The findings reveal that the PD and PDF controllers exhibit superior response characteristics, offering the fastest and most stable outcomes regardless of whether droop characteristics are utilized or filtering techniques are introduced. Although the implementation of filters significantly mitigates overshoot, it is evident that controllers incorporating droop characteristics tend to compromise optimal steady-state time stability. The overall analysis underscores the PD and PDF controllers as the preeminent solutions for ensuring frequency stability in hydraulic LFC systems, especially under abrupt and substantial load changes, thus positioning them as vital tools in enhancing hydraulic power system reliability and efficiency.

PRE-CORRECTION OF PHASE-FREQUENCY CHARACTERISTICS OF DIGITAL FILTERS

The article is devoted to the synthesis of a digital filter computer model with zero phase-frequency characteristic. A predetermined structural implementation of the digital filter with zero phase-frequency response is based on double filtering of the signal in the forward and reverse directions, as well as on filters with a finite impulse response. This article discusses the implementation of a filter with zero phase-frequency response based on filters with infinite impulse response. The implementation of pre-correction of the phase-frequency response of the filter is achieved due to the use of the two-channel structural diagram with the input signal spectrum transfer. The complexity of using filters with an infinite impulse response is associated with its nonlinearity, which requires pre-correction in order to linearize the phase-frequency response. The article discusses both a mathematical model of signal passage through a block diagram and a computer model in the Matlab-Simulink environment in static and dynamic modes.

Phase Coexistence in Hamiltonian Hybrid Particle-Field Theory Using a Multi-Gaussian Approach.

This study introduces an implementation of multiple Gaussian filters within the Hamiltonian hybrid particle-field (HhPF) theory, aimed at capturing phase coexistence phenomena in mesoscopic molecular simulations. By employing a linear combination of two Gaussians, we demonstrate that HhPF can generate potentials with attractive and steric components analogous to Lennard-Jones (LJ) potentials, which are crucial for modeling phase coexistence. We compare the performance of this method with the multi-Gaussian core model (MGCM) in simulating liquid-gas coexistence for a single-component system across various densities and temperatures. Our results show that HhPF effectively captures detailed information on phase coexistence and interfacial phenomena, including microconfiguration transitions and increased interfacial fluctuations at higher temperatures. Notably, the phase boundaries obtained from HhPF simulations align more closely with those of LJ systems compared to the MGCM results. This work advances the hybrid particle-field methodology to address phase coexistence without requiring modifications to the equation of state or introducing additional interaction energy functional terms, offering a promising approach for mesoscale molecular simulations of complex systems.

Advanced, Real-Time Programmable FPGA-Based Digital Filtering Unit for IR Detection Modules

This paper presents a programmable digital filtering unit dedicated to operating with signals from infrared (IR) detection modules. The designed device is quite useful for increasing the signal-to-noise ratio due to the reduction in noise and interference from detector–amplifier circuits or external radiation sources. Moreover, the developed device is flexible due to the possibility of programming the desired filter types and their responses. In the circuit, an advanced field-programmable gate array FPGA chip was used to ensure an adequate number of resources that are necessary to implement an effective filtration process. The proposed circuity was assisted by a 32-bit microcontroller to perform controlling functions and could operate at frequency sampling of up to 40 MSa/s with 16-bit resolution. In addition, in our application, the sampling frequency decimation enabled obtaining relatively narrow passband characteristics also in the low frequency range. The filtered signal was available in real time at the digital-to-analog converter output. In the paper, we showed results of simulations and real measurements of filters implementation in the FPGA device. Moreover, we also presented a practical application of the proposed circuit in cooperation with an InAsSb mid-IR detector module, where its self-noise was effectively reduced. The presented device can be regarded as an attractive alternative to the lock-in technique, artificial intelligence algorithms, or wavelet transform in applications where their use is impossible or problematic. Comparing the presented device with the previous proposal, a higher signal-to-noise ratio improvement and wider bandwidth of operation were obtained.

Vector space model, term frequency-inverse document frequency with linear search, and object-relational mapping Django on hadith data search

For Muslims, the Hadith ranks as the secondary legal authority following the Quran. This research leverages hadith data to streamline the search process within the nine imams’ compendium using the vector space model (VSM) approach. The primary objective of this research is to enhance the efficiency and effectiveness of the search process within Hadith collections by implementing pre-filtering techniques. This study aims to demonstrate the potential of linear search and Django object-relational mapping (ORM) filters in reducing search times and improving retrieval performance, thereby facilitating quicker and more accurate access to relevant Hadiths. Prior studies have indicated that VSM is efficient for large data sets because it assigns weights to every term across all documents, regardless of whether they include the search keywords. Consequently, the more documents there are, the more protracted the weighting phase becomes. To address this, the current research pre-filters documents prior to weighting, utilizing linear search and Django ORM as filters. Testing on 62,169 hadiths with 20 keywords revealed that the average VSM search duration was 51 seconds. However, with the implementation of linear and Django ORM filters, the times were reduced to 7.93 and 8.41 seconds, respectively. The recall@10 rates were 79% and 78.5%, with MAP scores of 0.819 and 0.814, accordingly.

Design and Implementation of High Speed and Low Power Filter

In order to solve the problems of complex structure and high power consumption of current sampling filter circuit, a high speed and low power Filter design scheme based on pipeline structure is proposed in this paper. This filter is composed of recursive CIC filter and FIR filter based on shift adder. The order of CIC filter and FIR filter can be adjusted according to the difference between the measured temperature and the threshold temperature range set by the user, thus the power consumption of the filter is reduced. The experimental results show that, under the same conditions, the utilization rate of the LUS is reduced by 86%, the power consumption is reduced by 88%, and the utilization rate of the LUS is reduced by 90% compared with the half-band comb filter, power consumption is reduced by 28%.

Design and Simulation of Three-Band Microstrip Resonator Bandpass Filters for Wireless Communication Systems

Abstract This research focuses on the design, simulation, and practical implementation of three-band microstrip resonator bandpass filters for wireless communication systems. Key parameters targeted in optimizing these filters include coupling coefficient, external quality factor, and fractional bandwidth, among others. Using ANSYS HFSS software, the electromagnetic behavior of the filters was analyzed to enhance their design. The proposed filters were fabricated on RT/Duroid 5880 substrate and experimentally validated using a vector network analyzer. Experimental results were compared with simulations, demonstrating satisfactory performance at specific frequencies relevant to Wi-Fi, 5G, and radar applications. Additionally, a comparative study with other similar filters from the literature was conducted to evaluate their performance.

Retraction Note: Implementation of efficient reconfigurable FIR filter with control logic for 5G applications

Retraction Note: Implementation of efficient reconfigurable FIR filter with control logic for 5G applications

England RCT of air filtration to prevent respiratory infections (including covid-19) in care homes

Abstract Context There is evidence that portable high-efficiency-particulate-air (HEPA) filtration units remove microbial particles from the air, but it is unclear whether this is sufficient to reduce infections in care home residents. Objectives To investigate the effectiveness of portable HEPA filtration units for winter respiratory infection episode reduction in care home residents. Study design and analysis: Cluster controlled trial with intention-to-treat analysis. Setting: 90 residential care homes for older adults in England. Population: Residents expected to reside in the care home for ≥1 month. Intervention care homes: Five HEPA filtration units in communal rooms and one HEPA filtration unit in 10 to 16 bedrooms. Control care homes: Usual care. Outcome measures: The primary outcome is the number of symptomatic winter respiratory infection episodes recorded by care home staff. Secondary outcomes: other infection measures; falls /near falls; laboratory confirmed infections; hospitalisations; and staff sickness. Process evaluation to assess intervention acceptability and implementation. Results Care homes were randomised between January 2022 and February 2024, 43 to intervention and 47 to usual care. Respectively, in intervention and control group care homes: 43% and 45% provided nursing care; 87% and 87% dementia care; and median (IQR) number of communal rooms were 4 (3-5) in both groups. 1126 residents were consented, of whom 31 (3%) moved away; 151 (13%) died; and 5 stopped participating. Primary outcome data is 98% complete with 175,318 'resident days' symptom data collected. Comparing intervention and control group residents: median (IQR) age was 88 (81-92) and 88 (82-92) years; 33% and 43% were receiving nursing care; 58% and 57% had dementia; frailty scores were 6 (4-7) and 6 (5-7); 94% and 94% received influenza; and 97% and 95% COVID vaccines. Conclusions Final analytic results of this world-first RCT will be available for the conference. Key messages • This world-first RCT using HEPA filters in care homes will report the evidence of effectiveness of respiratory infection episode reduction in care home residents. • The trial will inform policy makers about the effectiveness, acceptability and implementation of HEPA filters in care homes.

Design and implementation of low power multiplierless FIR filters on FPGA and ASIC

ABSTRACT This paper presents a low-power design and implementation approach for multiplierless FIR filters by reducing switching activity between filter coefficients using different optimisation algorithms. The objective function simultaneously minimises hamming distance between the consecutive filter coefficients, passband, and stopband ripples. Low-pass, high-pass, band-pass, and band-stop FIR filters of different order and word lengths are designed using improved grey-wolf optimisation. Comparison with grey-wolf optimisation, hybrid particle swarm optimisation, and grey-wolf optimisation, and whale optimisation algorithms is performed for different statistical parameters. The proposed filter is also compared with existing filter designs and shows considerable improvement in design metrics. For low-power implementation of designed FIR filters, carry-save-adder trees are utilised. FPGA and ASIC platforms are used for implementation. Basys-3 (Artix-7) FPGA board is targeted using the Vivado tool for FPGA implementation. Hardware design metrics such as slice LUTs, slice registers, slices, and dynamic power consumption are obtained. ASIC implementation is also performed using the Cadence Genus tool for a 45 nm Nan gate open cell library and total area, power, and delay are reported. The obtained results for FPGA slice utilisation and power consumption provide an average reduction of 61.39% and 74.13%, respectively. ASIC implementation provides an average 58.60% reduction in area-power product.