Search
112 articles for “signal extraction”
-
Entropy Analysis of EEG between Alcoholic and Control Subjects during Visual Stimulus Perception
Abstract: The purpose of this paper is to examine the variation in the EEG signal recorded from a group of individual, who were subjected under the effect of alcoholism while comparing them to non-alcoholic or controlled state. For the purpose, EEG from individuals was processed while subjects were perceiving visual picture stimulus from Snodgrass and Vanderwart picture set. A total of 10 trials for each subject have been considered in matched/non-matched …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 6, Issue 3, 2016 · pp. 5–14 Read article
-
Identification of individual ragas using artificial neural network classifier
Abstract: This paper presents the feature extraction as the base step of music information retrieval. Basic feature of music is chroma, which is extracted using from the music signal using spectrogram and chromagram. After the extraction of feature the comparison is made between the original data and extracted chroma data using neural network. Cite this ArticlePriya, Ravi Kumar. Identification of individual ragas using artificial neural network classifier. Journal of Artificial Intelligence …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 2, Issue 2, 2015 · pp. 24–28 Read article
-
APPLICATIONS OF VIRTUAL INSTRUMENTATION IN DIFFERENT DOMAINS OF EMBEDDED SYSTEMS
Abstract: This research work has intended to identify the clusters of embedded systems where the application ofvirtual instrumentation concept can be used; one can apply the concept of virtual instrumentation fordeveloping different applications of signal and image processing, automotive, mechatronics, control andsimulation, embedded software designing, HDL & microprocessor coding etc. The graphical tool used invirtual instrumentation such as LabVIEW can be used for designing various applications of differentembedded system domains. With …
Published in Journal of Control & Instrumentation · Vol. 1, Issue 1-2-3, 2011 · pp. 19–24 Read article
-
Depression Detection Using Machine Learning: A Comprehensive Review
Abstract: Depression remains one of the most prevalent mental health conditions globally, yet it frequently goes undiagnosed due to the reliance on subjective evaluation methods. With the growing availability of digital behavioral data and significant progress in machine learning (ML), new possibilities have emerged for the automated detection of depression. This review offers a detailed examination of recent advancements in ML-driven approaches to identifying depressive symptoms. It covers a range of …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 27–32 Read article
-
Graphene-Based Electronic Skin for Wearable Health Monitoring and Human–Machine Interaction, Materials, Structures, and AI Integration
Abstract: Graphene-based electronic skin (e-skin) has emerged as a transformative technology for next-generation wearable health monitoring and advanced human–machine interaction (HMI). Owing to its outstanding electrical conductivity, mechanical flexibility, atomic-scale thickness, and biocompatibility, graphene enables the fabrication of ultrathin, conformal, and multifunctional sensors capable of mimicking the sensory functions of natural human skin. Over the past decade, research in this domain has progressed rapidly across four interconnected fronts: material synthesis and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 175–180 Read article
-
AI Powered Fault Detection in DC Motor using STM32
Abstract: This work presents the design and implementation of an embedded artificial intelligence system for real-time fault detection in a direct current (DC) motor using the STM32 Nucleo- F411RE microcontroller. The objective of the study is to develop a low-cost and efficient predictive maintenance solution capable of identifying abnormal motor behavior at an early stage. Vibration and temperature signals are acquired using an MPU6050 sensor and processed directly on the microcontroller …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 39–49 Read article
-
Evaluation of Speech Recognition System for Security Purposes using Comparative Correlation Method
Abstract: Humans rely heavily on language for communication and most often, speech (oral) is one of the commonest means of communication. The speech recognition system is a smart system which grants access to users by recognizing the speech of the authorized user. Speech recognition is smart and precise in terms of authentication and validation. The problem with most security systems is imbalance pitch estimation, random noise and increment in theft due …
Published in Current Trends in Signal Processing · Vol. 12, Issue 3, 2022 · pp. 1–9 Read article
-
Application of Compressive Sensing for Sampling and Reconstruction of MRI Images
Abstract: In recent years, a new theory of compressive sensing has evolved which asserts that super resolved signals and images can be recovered with far fewer samples than that demanded by the Nyquist sampling theorem. It is required that the signal being sensed has a low information-rate meaning that it is sparse in original or some transform domain. Former approaches capture the complete signal and process it to extract the information. …
Published in Current Trends in Signal Processing · Vol. 6, Issue 2, 2016 · pp. 42–48 Read article
-
Classifying Abnormalities in Heartbeat Sound
Abstract: Heartbeat sounds play a major role in the detection of various diseases such as heart disease, hyperthyroidism, and high blood pressure in their early stages. In the proposed method, various abnormal and healthy heartbeat audio signals are given as input and the features are extracted using MFCC (mel-frequency cepstral coefficients). Then, a deep learning approach is applied in which the MFCC audio signals are sent to the CNN (convolutional neural …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 12, Issue 1, 2024 · pp. 24–31 Read article
-
Cutting- Edge Gravitational-Wave Detectors: Technology & Innovations
Abstract: Gravitational wave detectors using laser interferometry are sophisticated instruments designed to measure the ripples in spacetime caused by cosmic events such as the merging of black holes or neutron stars. This schematic outlines the fundamental components and working principle of a typical laser interferometric gravitational wave detector, such as those used in the LIGO and Virgo observatories. The core of the detector is an interferometer, typically a Michelson interferometer, with …
Published in International Journal of Universe · Vol. 1, Issue 1, 2025 · pp. 23–29 Read article
-
A Review Paper on The Mathematical Foundations of Artificial Intelligence
Abstract: Artificial Intelligence (AI) is deeply rooted in various branches of mathematics, which provide the theoretical foundation and practical tools for developing intelligent systems. This paper explores the crucial role of mathematics in AI, focusing on key areas such as Linear Algebra, Probability and Statistics, Optimization Techniques, Calculus, Graph Theory, and Fourier and Wavelet Transforms. Linear Algebra is fundamental for representing and manipulating data, with applications in dimensionality reduction and neural …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 7–14 Read article
-
Exploiting Phase of Speech Signal for Speaker Recognition
Abstract: Abstract—Performance of speaker recognition system with feature based on temporal phase is presented in this paper. In the state of the art spectral feature, Mel Frequency Cepstal Coefficient (MFCC) only magnitude of the Fourier Transform of speech signal is considered while phase is ignored. The cepstral coefficients extracted from temporal phase (MFTPC) of speech signal are used as features for speaker recognition system. The performance of MFTPC feature is evaluated …
Published in Journal of Communication Engineering & Systems · Vol. 9, Issue 2, 2019 · pp. 81–87 Read article
-
Feature Extraction and Analysis of Bearing Faults: A Review
Abstract: One of the most important steps in identifying bearing problems is feature extraction. In order to provide a more meaningful dataset, it entails locating and extracting pertinent features from raw bearing vibration signals. Tasks involving categorization and prediction can then make use of these attributes. In many practical applications, such as monitoring rotating machinery or electronic components, the raw signals collected (e.g., vibration, current, temperature) are often complex, high-dimensional, and …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 20–28 Read article
-
Fault Diagnosis of Air Compressor (AC) System using Local Mean Decomposition (LMD) and Logistic Regression (LR) Machine Learning Classifier
Abstract: This article presents a detailed and systematic procedure for performing fault diagnosis in an air compressor (AC) system by analyzing the audio signals generated during its operation. The analysis covers both normal (healthy) conditions and seven distinct types of faults, including bearing failure, flywheel malfunction, inlet valve leakage, outlet valve leakage, non-return valve failure, piston ring defect, and rider belt issues. To acquire the acoustic signals, the researchers utilized a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 416–427 Read article
-
An Approach of Multi-modal Biometric Iris and Speech based Person Recognition System with Decision Fusion Technique
Abstract: This paper presents a unique approach of multi-modal iris and speech feature based person recognition system. Iris images and speech signals are taken from CASIA iris database and NOIZEUS speech database respectively. Iris features are extracted after applying iris images noise removing and image pre-processing techniques. On the other hand, speech signal noise removing, start-end points detection algorithm, silence parts removal, windowing and feature extraction techniques are applied to extract …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 2, Issue 2, 2015 · pp. 5–10 Read article
-
AI Voice Detection Tool
Abstract: In today’s digital era, distinguishing between AI-generated and human voices is more important than ever. This project introduces an AI-based voice detection system designed to accurately identify synthetic voices, ensuring security and authenticity across various applications like cybersecurity, media verification, and fraud prevention.Our system works by analyzing incoming audio samples and comparing them against a diverse database of both AI-generated and real human voices. Using advanced machine learning and signal …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 1, 2026 · pp. 1–8 Read article
-
An Efficient Recursive Least Square (ERLS) Algorithm for Spectral Estimation with the Aid of Wavelet and Artificial Intelligence
Abstract: The spectral estimation technique is used for time frequency signal analysis, speech processing, and other signal processing applications. Some drawbacks of RLS algorithm are that it requires high computational power and the output obtained is numerically instability. So, the spectral efficiency of the signal is affected and a power error occurs in the estimator. In this paper, an efficient recursive least square (ERLS) algorithm is proposed for improving the power …
Published in Current Trends in Signal Processing · Vol. 2, Issue 1-3, 2012 · pp. 1–10 Read article
-
Speech Recognition and Analysis using Energy of the Signal
Abstract: AbstractSpeech plays an important role in day to day communication. It is a natural way to transfer thoughts from one to another. If any information needs to deliver in between human’s speech is the best way of delivery. With the help of the electronic system, we can extract the information from the original speech signal by doing signals processing. Here, in this research work, we formulate the system that recognizes …
Published in Current Trends in Signal Processing · Vol. 8, Issue 2, 2018 · pp. 25–33 Read article
-
Entropy Analysis Based Differential Evolution Approach for Emotion Classification for EEG
Abstract: Electroencephalography (EEG) signal processing is having its significance in various applications related to the emotion recognition and classification. The behavior monitoring, behavior class identification, emotion class identification are the major aspects for classification of EEG signal. In this paper, a feature adaptive differential evolution (DE) approach is defined to perform emotion classification. In this work, we used discrete wavelet transform (DWT), for extracting the statistical features from the EEG signal …
Published in Current Trends in Signal Processing · Vol. 5, Issue 3, 2015 · pp. 15–22 Read article
-
Cognitive Enhancement of the Brain: Removal of Artefacts
Abstract: The study aims to investigate and explore the various methods to find psychological and physiological signals of any subjects. Their pre and post data recordings are studied as a part of this study. The study is named as the “Cognitive Enhancement of the Brain.” Various features which are there in the physiological signals are actually processed to be extracted then classified and then interrelated or correlated by using various tools …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 2, 2018 · pp. 21–25 Read article