Objectives: In recent years, audio signal processing begins its outbreak on a global scale, which has altered the global market and has rapidly extended out as a fundamental design in various industries. Lifting based method is frequently implemented in many applications such as image processing and audio processing because it has some advantages that faster implementation with minimum computational cost.
Methods: In this proposed work, a Novel Lifting based Filter Bank (NLFB) is proposed using a modified variable filter aimed at digital hearing aid devices. This filter bank design has some mandatory constraints, such as hardware complexity, power consumption, and delay. The proposed method is designed with four lifting steps such as split, predict, update and merge to make the perfect reconstruction in analysis and decomposition in synthesis bank. The performance analysis of the proposed method is discussed in this article.
Results: The proposed method consumes less power, up to 45mW, and a minimum delay between 85ns and 91.1ns when compared to traditional methods.
Conclusion: The proposed design output consumes 32 % of minimum hardware components, 12% of low power compared to interpolated filter bank and 6% of delay is reduced using Modified Variable Filter (MVFB).
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http://dx.doi.org/10.1080/17434440.2022.2159376 | DOI Listing |
J Acoust Soc Am
January 2025
Department of Electronics Engineering, Pusan National University, Busan, South Korea.
The amount of information contained in speech signals is a fundamental concern of speech-based technologies and is particularly relevant in speech perception. Measuring the mutual information of actual speech signals is non-trivial, and quantitative measurements have not been extensively conducted to date. Recent advancements in machine learning have made it possible to directly measure mutual information using data.
View Article and Find Full Text PDFCogn Neurodyn
December 2025
Department of Electrical and Electronics Engineering, Jazan, 45142 Jazan Saudi Arabia.
Alzheimer's disease (AD) is a chronic disability that occurs due to the loss of neurons. The traditional methods to detect AD involve questionnaires and expensive neuro-imaging tests, which are time-consuming, subjective, and inconvenient to the target population. To overcome these limitations, Electroencephalogram (EEG) based methods have been developed to classify AD patients from normal controlled (NC) and mild cognitive impairment (MCI) subjects.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Computer Engineering, Gachon University, Sujeong-gu, Seongnam-si 13120, Republic of Korea.
Generating accurate and contextually rich captions for images and videos is essential for various applications, from assistive technology to content recommendation. However, challenges such as maintaining temporal coherence in videos, reducing noise in large-scale datasets, and enabling real-time captioning remain significant. We introduce MIRA-CAP (Memory-Integrated Retrieval-Augmented Captioning), a novel framework designed to address these issues through three core innovations: a cross-modal memory bank, adaptive dataset pruning, and a streaming decoder.
View Article and Find Full Text PDFInt J Mol Sci
December 2024
Institute for the Application of Nuclear Energy INEP, University of Belgrade, Banatska 31b, 11080 Belgrade, Serbia.
Thyroglobulin (Tg) is a reliable marker for detecting recurrence in differentiated thyroid cancer (DTC) patients, but frequently occurring Tg antibodies (TgAbs) can hinder accurate measurement. We aimed to develop a preanalytical protocol for precise Tg detection in TgAb presence using the immunoradiometric assay (IRMA) platform. This study involved forty-five patients who underwent IRMA Tg and radioimmunoassay (RIA) TgAb measurements, including two patients monitored for recurrence and one with confirmed recurrence.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Clinical Biochemistry, Faculty of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran.
This study explores the role of LINC00839 and its potential interaction with the miR-195-5p/cyclin E1 (CCNE1) axis in oral squamous cell carcinoma (OSCC). Using The Cancer Genome Atlas, we analyzed lncRNA, miRNA, and mRNA sequencing data for OSCC. Different online tools were applied to detect lncRNA-related miRNAs and their target mRNAs, forming a lncRNA/miRNA/mRNA axis.
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