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Emerging Machine Learning Techniques in Signal Processing
2008
EURASIP Journal on Advances in Signal Processing
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In the era of knowledge-based society and machine automation, there is a strong interest in machine learning (ML) techniques in a wide range of applications. ...
Adali extends previous works on using complex-valued calculus in order to implement nonlinear adaptive signal processing algorithms in the complex domain, as well as some procedures resulting from this ...
In the era of knowledge-based society and machine automation, there is a strong interest in machine learning (ML) techniques in a wide range of applications. ...
doi:10.1155/2008/830381
fatcat:nexw3dvvqzfkvnn6qcoaqegfwy
ML-ASPA: A Contemplation of Machine Learning-based Acoustic Signal Processing Analysis for Sounds, Strains Emerging Technology
[article]
2023
arXiv
pre-print
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, signal enhancement, feature extraction, sound localization, and machine learning techniques... ...
It chronicles historical progress in signal processing techniques that have facilitated the extraction of valuable information from bowel sounds, emphasizing advancements in noise reduction, segmentation ...
Machine learning (ML) techniques have emerged as a powerful solution to address these challenges, offering automated data processing and pattern recognition capabilities. ...
arXiv:2402.10005v1
fatcat:fs73ihqewzea3e6irppc7slmgu
Adaptation and learning over complex networks [From the Guest Editors]
2013
IEEE Signal Processing Magazine
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the signal processing community. ...
Extensive research efforts on information processing over graphs exist within other fields such as statistics, computer science, optimization, control, economics, machine learning, biological sciences, ...
The authors describe distributed techniques that enable nodes to infer the network topology from in-network distributed processing. 6) "The Emerging Field of Signal Processing on Graphs" by Shuman et al ...
doi:10.1109/msp.2013.2240191
fatcat:jz3cqtslkzbpxlqb3bsyxcrd3y
Trends in Machine Learning for Signal Processing [In the Spotlight]
2011
IEEE Signal Processing Magazine
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In addition to the SP, machine learning methods also began to be used to unravel the biological meaning of the signals and to categorize the evidence in meaningful ways. ...
The special issue on music SP in IEEE Journal of Selected Topics in Signal Processing (fall 2011) set the stage for current activities in this field. ...
doi:10.1109/msp.2011.942319
fatcat:brwvz3sjvrfyboqvieovxvfrd4
Guest Editorial: Special Issue on Machine Learning Methods in Signal Processing
2004
IEEE Transactions on Signal Processing
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While some of the rich literature on machine learning has penetrated the signal processing community in great depth, a variety of new techniques, which offer tremendous potential for signal processing ...
While Bayesian learning has had a rich tradition in the signal processing community, a number of related methods have emerged in the learning literature, enabling the development of a variety of robust ...
doi:10.1109/tsp.2004.831149
fatcat:hher6ezzkvdwharq3tln56ks6m
Grand Challenges in Signal Processing for Communications
2021
Frontiers in Signal Processing
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In this editorial article, we have outlined some important areas in emerging signal processing techniques for communications, including large-scale massive MIMO, Holographic MIMO, reconfigurable intelligent ...
hardware design and signal processing techniques (Basar et al., 2019) . ...
The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in ...
doi:10.3389/frsip.2021.664331
fatcat:rjc4f7ffjnhinbxhyb34frpmpy
Machine Learning for Pulsar Detection
2017
Proceedings of the International Astronomical Union
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In this paper we provide a summary of the emerging machine learning techniques being applied to this problem. ...
However, this will result in very large numbers of pulsar and transient event candidates and the associated data rates will be technically challenging in terms of data storage and signal processing. ...
Table 1 shows the evolution of automated candidate selection techniques over time with the most recent publications representing the state of the art in machine learning applications. ...
doi:10.1017/s1743921317009000
fatcat:ofvljqld3rfxta6lfn7gk3n424
A review of various techniques for vibration signal analysis to diagnose the faults of electric motors: Advantages and drawbacks
2023
Zenodo
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This scholarly article presents an extensive evaluation of diverse methodologies utilized in vibration signal analysis, emphasizing the merits and limitations associated with each technique. ...
The strategies covered include approaches based on machine learning as well as time-domain analysis, frequency-domain analysis, time-frequency analysis, and time-domain analysis. ...
in the fault classification of electric motors utilizing signal processing and machine learning. ...
doi:10.5281/zenodo.10669477
fatcat:xbhmjxm7f5hurjsd74v7ymegay
Highlights From the Machine Learning for Signal Processing Technical Committee [In the Spotlight]
2020
IEEE Signal Processing Magazine
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The Machine Learning for Signal Processing Technical Committee (MLSP TC), one of the 13 TCs in the IEEE Signal Processing Society (SPS), has its mission in promoting activities in the MLSP, such as through ...
In general, the scope of the MLSP covers ML and nonlinear signal processing methodologies targeting both longstanding and emergent signal processing applications of a broad range. ...
doi:10.1109/msp.2020.3018689
fatcat:pdy6jcbho5hd5biaxyonzmepsu
2021 Index IEEE Signal Processing Magazine Vol. 38
2021
IEEE Signal Processing Magazine
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-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021. ...
Note that the item title is found only under the primary entry in the Author Index. ...
Human Machine Interfaces in Upper-Limb Prosthesis Control: A Survey of Techniques for Preprocessing and Processing of Biosignals. ...
doi:10.1109/msp.2021.3124108
fatcat:ro6fkwa5nndw5i7c3lbq2zljpy
Monitoring and Predicting the Surface Generation and Surface Roughness in Ultraprecision Machining: A Critical Review
2021
Machines
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Recent advances in Industry 4.0 and machine learning are providing an effective means for the optimization of process parameters, particularly through in-process monitoring and prediction while avoiding ...
Nevertheless, the process requires an in-depth and comprehensive understanding of the machining system, such as diamond turning with various input parameters, tool features that are able to alter the machining ...
The basic steps in monitoring, such as various types of sensors, signal processing techniques, and machine learning algorithms, are discussed in Section 3. ...
doi:10.3390/machines9120369
fatcat:ts4zabtmmrfgtj75h4nxvrfiei
Utilizing Machine Learning for Signal Classification and Noise Reduction in Amateur Radio
[article]
2024
arXiv
pre-print
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In this paper, we explore the application of machine learning techniques for signal classification and noise reduction in amateur radio operations. ...
In the realm of amateur radio, the effective classification of signals and the mitigation of noise play crucial roles in ensuring reliable communication. ...
With the rapid advancements in machine learning techniques, there exists a promising opportunity to revolutionize signal processing in amateur radio. ...
arXiv:2402.17771v1
fatcat:putzqmkl3bairn73nxdthun6sy
The MNIST Database of Handwritten Digit Images for Machine Learning Research [Best of the Web]
2012
IEEE Signal Processing Magazine
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Digital Object Identifier 10.1109/MSP.2012.2211477 The MNIST Database of Handwritten Digit Images for Machine Learning Research Li Deng IEEE SIGNAL PROCESSING MAGAZINE [141] NOVEMBER 2012 1053-5888/12/ ...
Historically, to promote machine learning and pattern recognition research, several standard databases have emerged in which the handwritten digits are preprocessed, including segmentation and normalization ...
doi:10.1109/msp.2012.2211477
fatcat:vzzjejugtjazxjpimn36stilgy
ICETET-SIP-19 2019 Author Index
2019
2019 9th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-19)
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P D Gawande Smart City Solutions on Drainage, Unused Well and Garbage Alerting System for 2019 9th International Conference on Emerging Trends in Engineering and Technology -Signal and Information Processing ...
Trends in Engineering and Technology -Signal and Information Processing (ICETET-SIP-19)
Author Index
46
Anupa Kavale,
Coin Counting and Sorting Machine
46
Prachi Bramhe
Coin Counting and Sorting ...
doi:10.1109/icetet-sip-1946815.2019.9091995
fatcat:fhhwumczg5et3mxxgn7yqajt2y
Machine learning for brain signal analysis
2021
International Journal of Biology and Chemistry
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Machine learning (ML) is an effective tool for analysing signals from the human brain. ...
Machine Learning techniques provide new insight into the under anding of brain function in healthy subjects and patients with neurological and mental disorders. ...
Machine learning has made enormous progress in the last two decades largely due to the growth of computing power and the emergence of deep learning; and its techniques have proved to be a valuable tool ...
doi:10.26577/ijbch.2021.v14.i2.01
fatcat:z5qmxy5ssvbvtmafalknxokhly
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