Cognitive neurodynamic approaches to adaptive signal processing in wireless sensor networks

In recent years, Wireless Sensor Networks (WSN) have become vital because of their versatility in numerous applications. Nevertheless, the attain problems like inherent noise, and limited node computation capabilities, result in reduced sensor node lifespan as well as enhanced power consumption. To...

Full description

Saved in:

Bibliographic Details
Published in:	Cognitive neurodynamics Vol. 19; no. 1; p. 11
Main Authors:	Shanthi, K. G., Kinol, A. Mary Joy, Devi, S. Rukmani, Kannan, K.
Format:	Journal Article
Language:	English
Published:	Dordrecht Springer Netherlands 01.12.2025 Springer Nature B.V
Subjects:	Algorithms Architecture Arithmetic Arithmetic coding Artificial Intelligence Binary codes Biochemistry Biomedical and Life Sciences Biomedicine Cognitive Psychology Comparative analysis Computer Science Data processing Data transmission Decision trees Deep learning Energy consumption Energy efficiency Impulse response Information processing Innovations Life span Lookup tables Neurosciences Noise reduction Optimization techniques Partial differential equations Power consumption Research Article Sensors Signal processing Wireless sensor networks Offset binary coding Look-up tables Modified distributed arithmetic Adaptive finite impulse response Least mean squares Multiply and accumulate
ISSN:	1871-4080, 1871-4099
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	In recent years, Wireless Sensor Networks (WSN) have become vital because of their versatility in numerous applications. Nevertheless, the attain problems like inherent noise, and limited node computation capabilities, result in reduced sensor node lifespan as well as enhanced power consumption. To tackle such problems, this study develops a Modified-Distributed Arithmetic-Offset Binary Coding-based Adaptive Finite Impulse Response (MDA-OBC based AFIR) framework. By leveraging Modified Distributed Arithmetic (MDA) which optimizes arithmetic operations by replacing the multipliers with lookup tables (LUT) hence minimizing energy consumption as well as computational complexity. Offset Binary Coding (OBC) enhanced the efficiency of data transmission by minimizing the data representation overhead. In addition to this, the adaptive strategy is incorporated with the Adaptive Finite Impulse Response (AFIR) framework permitting the filters to dynamically adjust to varying signal characteristics, thus offering high noise suppression and low distortion rates. Comprehensive simulations and comparative analysis validate the effectiveness of the proposed MDA-OBC-based AFIR method. The proposed method attained a lower energy consumption of 1.5 J and 130 W power consumption than the traditional implementations, resulting in significant energy efficiency and data transmission in signal preprocessing and noise suppression in WSNs.
AbstractList	In recent years, Wireless Sensor Networks (WSN) have become vital because of their versatility in numerous applications. Nevertheless, the attain problems like inherent noise, and limited node computation capabilities, result in reduced sensor node lifespan as well as enhanced power consumption. To tackle such problems, this study develops a Modified-Distributed Arithmetic-Offset Binary Coding-based Adaptive Finite Impulse Response (MDA-OBC based AFIR) framework. By leveraging Modified Distributed Arithmetic (MDA) which optimizes arithmetic operations by replacing the multipliers with lookup tables (LUT) hence minimizing energy consumption as well as computational complexity. Offset Binary Coding (OBC) enhanced the efficiency of data transmission by minimizing the data representation overhead. In addition to this, the adaptive strategy is incorporated with the Adaptive Finite Impulse Response (AFIR) framework permitting the filters to dynamically adjust to varying signal characteristics, thus offering high noise suppression and low distortion rates. Comprehensive simulations and comparative analysis validate the effectiveness of the proposed MDA-OBC-based AFIR method. The proposed method attained a lower energy consumption of 1.5 J and 130 W power consumption than the traditional implementations, resulting in significant energy efficiency and data transmission in signal preprocessing and noise suppression in WSNs. In recent years, Wireless Sensor Networks (WSN) have become vital because of their versatility in numerous applications. Nevertheless, the attain problems like inherent noise, and limited node computation capabilities, result in reduced sensor node lifespan as well as enhanced power consumption. To tackle such problems, this study develops a Modified-Distributed Arithmetic-Offset Binary Coding-based Adaptive Finite Impulse Response (MDA-OBC based AFIR) framework. By leveraging Modified Distributed Arithmetic (MDA) which optimizes arithmetic operations by replacing the multipliers with lookup tables (LUT) hence minimizing energy consumption as well as computational complexity. Offset Binary Coding (OBC) enhanced the efficiency of data transmission by minimizing the data representation overhead. In addition to this, the adaptive strategy is incorporated with the Adaptive Finite Impulse Response (AFIR) framework permitting the filters to dynamically adjust to varying signal characteristics, thus offering high noise suppression and low distortion rates. Comprehensive simulations and comparative analysis validate the effectiveness of the proposed MDA-OBC-based AFIR method. The proposed method attained a lower energy consumption of 1.5 J and 130 W power consumption than the traditional implementations, resulting in significant energy efficiency and data transmission in signal preprocessing and noise suppression in WSNs.In recent years, Wireless Sensor Networks (WSN) have become vital because of their versatility in numerous applications. Nevertheless, the attain problems like inherent noise, and limited node computation capabilities, result in reduced sensor node lifespan as well as enhanced power consumption. To tackle such problems, this study develops a Modified-Distributed Arithmetic-Offset Binary Coding-based Adaptive Finite Impulse Response (MDA-OBC based AFIR) framework. By leveraging Modified Distributed Arithmetic (MDA) which optimizes arithmetic operations by replacing the multipliers with lookup tables (LUT) hence minimizing energy consumption as well as computational complexity. Offset Binary Coding (OBC) enhanced the efficiency of data transmission by minimizing the data representation overhead. In addition to this, the adaptive strategy is incorporated with the Adaptive Finite Impulse Response (AFIR) framework permitting the filters to dynamically adjust to varying signal characteristics, thus offering high noise suppression and low distortion rates. Comprehensive simulations and comparative analysis validate the effectiveness of the proposed MDA-OBC-based AFIR method. The proposed method attained a lower energy consumption of 1.5 J and 130 W power consumption than the traditional implementations, resulting in significant energy efficiency and data transmission in signal preprocessing and noise suppression in WSNs. In recent years, Wireless Sensor Networks (WSN) have become vital because of their versatility in numerous applications. Nevertheless, the attain problems like inherent noise, and limited node computation capabilities, result in reduced sensor node lifespan as well as enhanced power consumption. To tackle such problems, this study develops a Modified-Distributed Arithmetic-Offset Binary Coding-based Adaptive Finite Impulse Response (MDA-OBC based AFIR) framework. By leveraging Modified Distributed Arithmetic (MDA) which optimizes arithmetic operations by replacing the multipliers with lookup tables (LUT) hence minimizing energy consumption as well as computational complexity. Offset Binary Coding (OBC) enhanced the efficiency of data transmission by minimizing the data representation overhead. In addition to this, the adaptive strategy is incorporated with the Adaptive Finite Impulse Response (AFIR) framework permitting the filters to dynamically adjust to varying signal characteristics, thus offering high noise suppression and low distortion rates. Comprehensive simulations and comparative analysis validate the effectiveness of the proposed MDA-OBC-based AFIR method. The proposed method attained a lower energy consumption of 1.5 J and 130 W power consumption than the traditional implementations, resulting in significant energy efficiency and data transmission in signal preprocessing and noise suppression in WSNs.
ArticleNumber	11
Author	Kannan, K. Shanthi, K. G. Kinol, A. Mary Joy Devi, S. Rukmani
Author_xml	– sequence: 1 givenname: K. G. surname: Shanthi fullname: Shanthi, K. G. organization: Department of Electronics and Communication Engineering, R.M.K. College of Engineering and Technology – sequence: 2 givenname: A. Mary Joy surname: Kinol fullname: Kinol, A. Mary Joy email: alphonse.kinol@gmail.com organization: Department of Electronics and Communication Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University – sequence: 3 givenname: S. Rukmani surname: Devi fullname: Devi, S. Rukmani organization: Department of Electronics and Communication Engineering, R.M.D Engineering College – sequence: 4 givenname: K. surname: Kannan fullname: Kannan, K. organization: Department of Electronics and Communication Engineering, R.M.K. College of Engineering and Technology
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/39801917$$D View this record in MEDLINE/PubMed
BookMark	eNp9kctOxCAUhonReH8BF6aJGzdVKKXA0ky8JSZudOWCID0d0Q6MnNaJby_OeElcuAIO33dy4N8h6yEGIOSA0RNGqTxFxoRkJa3qklGmacnWyDZTuVRTrdd_9opukR3EZ0pFo1i9Sba4Vllgcps8TOI0-MG_QRFgTLF9D3bmXWHn8xStewIshljY1s6XDPppsH2R7xwg-jAtfCgWPkGfjwVCwJhyo2ER0wvukY3O9gj7X-suub84v5tclTe3l9eTs5vScSmGUnJXgbRt7bTquGrACSXrppO10lbWQrnGSmmdaKCtKH_koDotukZBQ6uOab5Ljld981ivI-BgZh4d9L0NEEc0nIlaKV0pkdGjP-hzHFN-0pLiXHK6pA6_qPFxBq2ZJz-z6d18f1sG1ApwKSIm6Izzgx18DEOyvjeMms-EzCohkxMyy4QMy2r1R_3u_q_EVxJmOEwh_Y79j_UBbEujDA
CitedBy_id	crossref_primary_10_1109_JIOT_2025_3532749
Cites_doi	10.1016/j.prime.2023.100148 10.3390/electronics11193118 10.1007/s00034-023-02567-0 10.3390/s23031573 10.3390/electronics12010180 10.37965/jait.2023.0149 10.3390/electronics10161937 10.1002/cpe.5949 10.3390/electronics10070862 10.1016/j.iot.2023.100813 10.3390/s22239043 10.3390/app12052757 10.1109/TEVC.2022.3215743 10.1002/dac.5467 10.1109/TEVC.2024.3417416 10.3390/mi15040440 10.1016/j.swevo.2024.101535 10.1007/s12046-022-02013-y 10.1109/TEVC.2015.2458037 10.1016/j.engappai.2023.105971 10.3390/electronics12102317 10.1109/TCSI.2022.3227727 10.1109/ACCESS.2023.3293422
ContentType	Journal Article
Copyright	The Author(s), under exclusive licence to Springer Nature B.V. 2025 Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. The Author(s), under exclusive licence to Springer Nature B.V. 2025. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Copyright Springer Nature B.V. Dec 2025
Copyright_xml	– notice: The Author(s), under exclusive licence to Springer Nature B.V. 2025 Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. – notice: The Author(s), under exclusive licence to Springer Nature B.V. 2025. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. – notice: Copyright Springer Nature B.V. Dec 2025
DBID	AAYXX CITATION NPM JQ2 K9. 7X8
DOI	10.1007/s11571-024-10190-1
DatabaseName	CrossRef PubMed ProQuest Computer Science Collection ProQuest Health & Medical Complete (Alumni) MEDLINE - Academic
DatabaseTitle	CrossRef PubMed ProQuest Health & Medical Complete (Alumni) ProQuest Computer Science Collection MEDLINE - Academic
DatabaseTitleList	MEDLINE - Academic ProQuest Health & Medical Complete (Alumni) PubMed
Database_xml	– sequence: 1 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Anatomy & Physiology Computer Science Architecture
EISSN	1871-4099
ExternalDocumentID	39801917 10_1007_s11571_024_10190_1
Genre	Journal Article
GroupedDBID	--- .86 .VR 06C 06D 0R~ 0VY 1N0 203 29F 29~ 2J2 2JN 2JY 2KG 2KM 2LR 2WC 2~H 30V 4.4 406 408 409 40D 40E 53G 5GY 67N 67Z 6NX 875 8TC 95- 95. 95~ 96X AAAVM AABHQ AACDK AAHNG AAIAL AAJBT AAJKR AANZL AAPKM AARTL AASML AATNV AATVU AAUYE AAWCG AAYIU AAYQN AAYTO ABAKF ABBRH ABBXA ABDBE ABDZT ABECU ABFSG ABFTD ABFTV ABHLI ABHQN ABIVO ABJNI ABJOX ABKCH ABMNI ABMQK ABNWP ABPLI ABQBU ABRTQ ABSXP ABTEG ABTHY ABTKH ABTMW ABWNU ABXPI ACAOD ACDTI ACGFS ACHSB ACHXU ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACPRK ACSTC ACZOJ ADBBV ADHHG ADHIR ADKFA ADKNI ADKPE ADRFC ADTPH ADURQ ADYFF ADZKW AEFQL AEGAL AEGNC AEJHL AEJRE AEMSY AENEX AEOHA AEPYU AETLH AEVLU AEXYK AEZWR AFBBN AFDZB AFHIU AFLOW AFOHR AFQWF AFWTZ AFZKB AGAYW AGDGC AGJBK AGMZJ AGQEE AGQMX AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHPBZ AHWEU AHYZX AIAKS AIGIU AIIXL AILAN AITGF AIXLP AJRNO AJZVZ AKMHD ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMXSW AMYLF AMYQR AOCGG AOIJS ARMRJ ATHPR AXYYD AYFIA B-. BA0 BAWUL BGNMA CS3 CSCUP DDRTE DNIVK DPUIP DU5 EBLON EBS EIOEI ESBYG F5P FERAY FFXSO FIGPU FNLPD FRRFC FWDCC G-Y G-Z GGCAI GGRSB GJIRD GNWQR GQ7 GQ8 GX1 GXS HF~ HG5 HG6 HLICF HMJXF HQYDN HRMNR HZ~ IJ- IKXTQ IWAJR IXC IXD IXE IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ KDC KOV KPH LLZTM M4Y MA- NPVJJ NQJWS NU0 O93 O9I O9J OAM OK1 P2P PF0 PT4 QOR QOS R89 R9I ROL RPM RPX RSV S16 S1Z S27 S3A S3B SAP SBL SDH SHX SISQX SJYHP SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW SSXJD STPWE SZN T13 TR2 TSG TSK TSV TUC U2A U9L UG4 UOJIU UTJUX UZXMN VC2 VFIZW W48 WJK WK8 YLTOR Z45 ZMTXR ZOVNA ~A9 -Y2 2VQ 5VS 7X7 8FI 8FJ AANXM AARHV AAYXX ABULA ABUWG AEBTG AEKMD AFFHD AFGCZ AFKRA AHSBF AJBLW ARAPS BBNVY BDATZ BENPR BGLVJ BHPHI CAG CCPQU CITATION COF DIK EJD EN4 FINBP FSGXE FYUFA H13 HCIFZ HMCUK HYE K7- M7P O9- OVD PHGZM PHGZT PQGLB PSYQQ TEORI UKHRP AAYZH AESKC NPM JQ2 K9. 7X8
ID	FETCH-LOGICAL-c375t-73c2e7ad4c98f386ec58746f7489a7458c6a77ac56ed203b3e8f95f68e602f193
IEDL.DBID	RSV
ISICitedReferencesCount	1
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001393550700012&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	1871-4080
IngestDate	Fri Sep 05 08:10:40 EDT 2025 Wed Nov 26 14:53:40 EST 2025 Mon Jul 21 05:31:38 EDT 2025 Tue Nov 18 21:22:43 EST 2025 Sat Nov 29 04:10:24 EST 2025 Wed Dec 10 14:46:37 EST 2025
IsPeerReviewed	true
IsScholarly	true
Issue	1
Keywords	Offset binary coding Look-up tables Modified distributed arithmetic Adaptive finite impulse response Least mean squares Multiply and accumulate
Language	English
License	The Author(s), under exclusive licence to Springer Nature B.V. 2025. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c375t-73c2e7ad4c98f386ec58746f7489a7458c6a77ac56ed203b3e8f95f68e602f193
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
PMID	39801917
PQID	3153373085
PQPubID	2043944
ParticipantIDs	proquest_miscellaneous_3154889285 proquest_journals_3153373085 pubmed_primary_39801917 crossref_citationtrail_10_1007_s11571_024_10190_1 crossref_primary_10_1007_s11571_024_10190_1 springer_journals_10_1007_s11571_024_10190_1
PublicationCentury	2000
PublicationDate	2025-12-01
PublicationDateYYYYMMDD	2025-12-01
PublicationDate_xml	– month: 12 year: 2025 text: 2025-12-01 day: 01
PublicationDecade	2020
PublicationPlace	Dordrecht
PublicationPlace_xml	– name: Dordrecht – name: Netherlands
PublicationTitle	Cognitive neurodynamics
PublicationTitleAbbrev	Cogn Neurodyn
PublicationTitleAlternate	Cogn Neurodyn
PublicationYear	2025
Publisher	Springer Netherlands Springer Nature B.V
Publisher_xml	– name: Springer Netherlands – name: Springer Nature B.V
References	SL Chen (10190_CR2) 2023; 23 TP Dinh (10190_CR6) 2023; 22 KS Reddy (10190_CR17) 2022; 11 Y Zhang (10190_CR23) 2021; 10 S Janwadkar (10190_CR10) 2023; 4 Y Wu (10190_CR21) 2023; 3 YJ Cha (10190_CR1) 2023; 121 Y Wu (10190_CR20) 2022; 28 H Ding (10190_CR5) 2020; 32 R Swetha (10190_CR19) 2024; 43 K Lee (10190_CR14) 2023; 12 R Dong (10190_CR7) 2021; 22 VC Gogineni (10190_CR9) 2022; 70 H Ding (10190_CR4) 2024; 89 A Nimbekar (10190_CR15) 2023 Y Wu (10190_CR22) 2024 JM Pak (10190_CR16) 2022; 12 A Gupta (10190_CR8) 2015; 20 RL Chung (10190_CR3) 2021; 10 A Kavitha (10190_CR11) 2023; 36 B Kwon (10190_CR13) 2022; 12 M Sun (10190_CR18) 2024; 15 JCR Kumar (10190_CR12) 2022; 47
References_xml	– volume: 4 start-page: 100148 year: 2023 ident: 10190_CR10 publication-title: e- Prime-Adv Electr Eng Electr Energy doi: 10.1016/j.prime.2023.100148 – volume: 11 start-page: 3118 issue: 19 year: 2022 ident: 10190_CR17 publication-title: Electronics doi: 10.3390/electronics11193118 – volume: 43 start-page: 1993 issue: 4 year: 2024 ident: 10190_CR19 publication-title: Circ Syst Signal Pr doi: 10.1007/s00034-023-02567-0 – volume: 23 start-page: 1573 issue: 3 year: 2023 ident: 10190_CR2 publication-title: Sens doi: 10.3390/s23031573 – volume: 12 start-page: 180 issue: 1 year: 2022 ident: 10190_CR16 publication-title: Electronics doi: 10.3390/electronics12010180 – volume: 3 start-page: 32 issue: 1 year: 2023 ident: 10190_CR21 publication-title: J Artif Intell Technol doi: 10.37965/jait.2023.0149 – volume: 10 start-page: 1937 issue: 16 year: 2021 ident: 10190_CR23 publication-title: Electronics doi: 10.3390/electronics10161937 – volume: 32 issue: 24 year: 2020 ident: 10190_CR5 publication-title: Concurr Comput Pract Exp doi: 10.1002/cpe.5949 – volume: 10 start-page: 862 issue: 7 year: 2021 ident: 10190_CR3 publication-title: Electronics doi: 10.3390/electronics10070862 – volume: 22 year: 2023 ident: 10190_CR6 publication-title: Internet of Things doi: 10.1016/j.iot.2023.100813 – volume: 22 start-page: 9043 issue: 23 year: 2021 ident: 10190_CR7 publication-title: Sens doi: 10.3390/s22239043 – volume: 12 start-page: 2757 issue: 5 year: 2022 ident: 10190_CR13 publication-title: Appl Sci doi: 10.3390/app12052757 – volume: 28 start-page: 62 issue: 1 year: 2022 ident: 10190_CR20 publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2022.3215743 – volume: 36 issue: 8 year: 2023 ident: 10190_CR11 publication-title: Int J Commun Syst doi: 10.1002/dac.5467 – year: 2024 ident: 10190_CR22 publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2024.3417416 – volume: 15 start-page: 440 issue: 4 year: 2024 ident: 10190_CR18 publication-title: Micromachines doi: 10.3390/mi15040440 – volume: 89 year: 2024 ident: 10190_CR4 publication-title: Swarm Evol Comput doi: 10.1016/j.swevo.2024.101535 – volume: 47 start-page: 248 issue: 4 year: 2022 ident: 10190_CR12 publication-title: Sādhanā doi: 10.1007/s12046-022-02013-y – volume: 20 start-page: 343 issue: 3 year: 2015 ident: 10190_CR8 publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2015.2458037 – volume: 121 year: 2023 ident: 10190_CR1 publication-title: Eng Appl Artif Intell doi: 10.1016/j.engappai.2023.105971 – volume: 12 start-page: 2317 issue: 10 year: 2023 ident: 10190_CR14 publication-title: Electronics doi: 10.3390/electronics12102317 – volume: 70 start-page: 833 issue: 2 year: 2022 ident: 10190_CR9 publication-title: IEEE TCAS-I doi: 10.1109/TCSI.2022.3227727 – year: 2023 ident: 10190_CR15 publication-title: IEEE Access doi: 10.1109/ACCESS.2023.3293422
SSID	ssj0056814
Score	2.3831851
Snippet	In recent years, Wireless Sensor Networks (WSN) have become vital because of their versatility in numerous applications. Nevertheless, the attain problems like...
SourceID	proquest pubmed crossref springer
SourceType	Aggregation Database Index Database Enrichment Source Publisher
StartPage	11
SubjectTerms	Algorithms Architecture Arithmetic Arithmetic coding Artificial Intelligence Binary codes Biochemistry Biomedical and Life Sciences Biomedicine Cognitive Psychology Comparative analysis Computer Science Data processing Data transmission Decision trees Deep learning Energy consumption Energy efficiency Impulse response Information processing Innovations Life span Lookup tables Neurosciences Noise reduction Optimization techniques Partial differential equations Power consumption Research Article Sensors Signal processing Wireless sensor networks
Title	Cognitive neurodynamic approaches to adaptive signal processing in wireless sensor networks
URI	https://link.springer.com/article/10.1007/s11571-024-10190-1 https://www.ncbi.nlm.nih.gov/pubmed/39801917 https://www.proquest.com/docview/3153373085 https://www.proquest.com/docview/3154889285
Volume	19
WOSCitedRecordID	wos001393550700012&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVAVX databaseName: SpringerLink Journals customDbUrl: eissn: 1871-4099 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0056814 issn: 1871-4080 databaseCode: RSV dateStart: 20070301 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LS8QwEB58Hbz4Wh-rq0QQL1po06ZJj7IonkTwwYKHkqYJLGh32a6C_95J2uwiPkCPpdNkyGMyXzPzDcBJSKWhUWECVYgiSGTEAqGLNDDou-L5KMswKl2xCX5zIwaD7LZNCqt9tLu_knSWep7sFjGO0JcmaDpsAjRinmVm2WYsRr979PbXMmq5u2SEAoiORNimynzfxufj6IuP-eV-1B07V-v_U3gD1lo3k1w062ITFnS1BZ2LCiH2yzs5JS7w0_1R34J1X9mBtBu9A099H1VEHOFl2dStJ56BXNdkOiKylGMnY4NAsLdxk3SAOpJhRSwJ8jM-khqR8miCDbmA83obHq4u7_vXQVuGIVAxZ9OAx4pqLstEZcLEItWKCZ6kxvLWSJ4woVLJuVQs1SUN4yLWwmTMpEKnITXoIO7AUjWq9B6QMsoYowKHR6rEqEJmukwiNJoI_EJDWRciPxu5ajnKbamM53zOrmwHNcdBzd2g5lEXzmbfjBuGjl-le36S83a31nlsnV40dQIVOJ69xn1mL09kpUevTgZtHSqKMrvN4ph1F2d4ziPu7cK5Xwnzxn_WZf9v4gewSm3xYRdL04Ol6eRVH8KKepsO68kRLPKBOHI74QNj4gAa
linkProvider	Springer Nature
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3da9swED9GO9he2i3ZunTppkHpy2qwZcuSH0tYyFgaCktHYA9GliUoZE6Ik8L--51kK2GkK3SPxmfpOEmn-_m-AM5DKg2NChOoQhRBIiMWCF2kgUHbFe9HWYZR6ZpN8MlEzGbZTZsUVvtod--SdJp6l-wWMY7QlyaoOmwCNGKew8S22bEY_fsPr39tRS3nS0YogOhIhG2qzMNj_H0d7dmYe_5Rd-0Mj_-P4Vdw1JqZ5KrZF6_hma460L2qEGL_-k0uiAv8dH_UO3DsOzuQ9qB34efARxURV_CybPrWE1-BXNdkvSCylEtHY4NAcLZlk3SAPJK7itgiyHN8JDUi5cUKB3IB5_UbuB1-mQ5GQduGIVAxZ-uAx4pqLstEZcLEItWKCZ6kxtatkTxhQqWSc6lYqksaxkWshcmYSYVOQ2rQQHwLB9Wi0u-AlFHGGBUoHqkSowqZ6TKJUGki8AsNZT2I_Grkqq1RbltlzPNddWUr1ByFmjuh5lEPPm-_WTYVOh6l7vtFztvTWuexNXpR1Qlk4NP2NZ4z6zyRlV5sHA3qOmQUaU6azbGdLs7wnkfc24NLvxN2g_-bl9OnkX-EF6Pp9Tgff518ew8vqW1E7OJq-nCwXm30GTxX9-u7evXBnYc_Y7oCFg
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3rS9xAEB-KLcUv1fo8H3UL4hcNl2yy2c1HUY-KckhtRfBD2OwDBM0dl1jwv-_sJrmz-IDix5DJ7rCP2fllZ34DsBtSaWlU2EAVoggSGbFAmCINLPqueD5KHUbaF5vgw6G4vs4unmTx-2j37kqyyWlwLE1l3R9r258lvkWMIwymCZoRlwyN-OdjgkjGBXX9vLzqbLFj1_L3yggLECmJsE2bebmNf4-mZ_7ms7tSfwQNFt6v_CJ8ad1Pctisl6_wwZRLsHxYIvS-fyR7xAeE-j_tS7DQVXwgrQFYhpujLtqIeCJM3dSzJx0zualIPSJSy7GXccEh2Nu4SUZAfcltSRw58h0-kgoR9GiCDflA9GoFfg9Ofh39CNryDIGKOasDHitquNSJyoSNRWoUEzxJreOzkTxhQqWSc6lYajQN4yI2wmbMpsKkIbXoOK7CXDkqzToQHWWMUYHDI1ViVSEzo5MIjSkCwtBS1oOom5lctdzlroTGXT5jXXaDmuOg5n5Q86gH-9Nvxg1zx5vSW92E5-0urvLYOcNoAgUq8H36Gvefu1SRpRk9eBm0gagoyqw1C2XaXZzh-Y94uAcH3aqYNf66Lhv_J74Dny-OB_n56fBsE-apq0_sw222YK6ePJht-KT-1LfV5JvfGn8BdAQK-g
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Cognitive+neurodynamic+approaches+to+adaptive+signal+processing+in+wireless+sensor+networks&rft.jtitle=Cognitive+neurodynamics&rft.au=Shanthi%2C+K.+G.&rft.au=Kinol%2C+A.+Mary+Joy&rft.au=Devi%2C+S.+Rukmani&rft.au=Kannan%2C+K.&rft.date=2025-12-01&rft.pub=Springer+Netherlands&rft.issn=1871-4080&rft.eissn=1871-4099&rft.volume=19&rft.issue=1&rft_id=info:doi/10.1007%2Fs11571-024-10190-1&rft.externalDocID=10_1007_s11571_024_10190_1
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1871-4080&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1871-4080&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1871-4080&client=summon