Class information for:
Level 1: CONTINUOUS ATTRACTORS//HAMMING MAXNET//K WINNER MACHINE

Basic class information
Class id #P Avg. number of
references		 Database coverage
of references
27847 219 23.5 56%


Bar chart of Publication_year

Last years might be incomplete

Hierarchy of classes
The table includes all classes above and classes immediately below the current class.


Cluster id Level Cluster label #P
9 4 COMPUTER SCIENCE, THEORY & METHODS//COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE//COMPUTER SCIENCE, INFORMATION SYSTEMS 1247339
211 3       COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE//IEEE TRANSACTIONS ON NEURAL NETWORKS//DATA MINING 51632
695 2             IEEE TRANSACTIONS ON NEURAL NETWORKS//EXTREME LEARNING MACHINE//NEURAL NETWORKS 13054
27847 1                   CONTINUOUS ATTRACTORS//HAMMING MAXNET//K WINNER MACHINE 219

Terms with highest relevance score


rank Term termType Chi square Shr. of publ. in
class containing
term		 Class's shr. of
term's tot. occurrences		 #P with
term in
class
1 CONTINUOUS ATTRACTORS authKW 686423 4% 62% 8
2 HAMMING MAXNET authKW 418293 1% 100% 3
3 K WINNER MACHINE authKW 418293 1% 100% 3
4 K WINNERS TAKE ALL authKW 371813 2% 67% 4
5 WINNER TAKE ALL authKW 350367 8% 15% 17
6 BACKGROUND NEURAL NETWORKS authKW 278862 1% 100% 2
7 CONTINUOUS TIME HOPFIELD NETWORK authKW 278862 1% 100% 2
8 DYNAMIC SHIFT authKW 278862 1% 100% 2
9 KWTA authKW 278862 1% 100% 2
10 LARGE GAIN BEHAVIOR authKW 278862 1% 100% 2

Web of Science journal categories


Rank Term Chi square Shr. of publ. in
class containing
term		 Class's shr. of
term's tot. occurrences		 #P with
term in
class
1 Computer Science, Artificial Intelligence 4497 37% 0% 82
2 Engineering, Electrical & Electronic 1554 49% 0% 108
3 Computer Science, Hardware & Architecture 392 8% 0% 17
4 Neurosciences 276 22% 0% 49
5 Computer Science, Theory & Methods 212 9% 0% 20
6 Computer Science, Cybernetics 177 3% 0% 6
7 Computer Science, Information Systems 15 3% 0% 6
8 Logic 8 0% 0% 1
9 Mathematical & Computational Biology 7 1% 0% 3
10 Mathematics, Applied 7 4% 0% 8

Address terms


Rank Term Chi square Shr. of publ. in
class containing
term		 Class's shr. of
term's tot. occurrences		 #P with
term in
class
1 BRAIN ENGN 185907 1% 67% 2
2 EEMCS DIMES 139431 0% 100% 1
3 MICROELECT CNM 139431 0% 100% 1
4 NEUROSCI BEHAV NUCLEUS 139431 0% 100% 1
5 SIGNAUX SYST DISTRIBUES INTELLIGENCE ARTIFI 139431 0% 100% 1
6 ETA ASIC DESIGN 69714 0% 50% 1
7 THAYER ENGN COMP SCI 69714 0% 50% 1
8 UNIV ECATEPEC VALLE TEOTIHUACAN 69714 0% 50% 1
9 VLSI SIGNAL PROC 69714 0% 50% 1
10 IMAGE PROC INTELLIGENT 46476 0% 33% 1

Journals


Rank Term Chi square Shr. of publ. in
class containing
term		 Class's shr. of
term's tot. occurrences		 #P with
term in
class
1 IEEE TRANSACTIONS ON NEURAL NETWORKS 59196 16% 1% 35
2 NEURAL COMPUTATION 22180 9% 1% 20
3 NEURAL NETWORKS 12791 8% 1% 17
4 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 4710 3% 1% 6
5 NEURAL PROCESSING LETTERS 3565 2% 1% 5
6 IEE PROCEEDINGS-CIRCUITS DEVICES AND SYSTEMS 2444 2% 0% 4
7 NEUROCOMPUTING 2083 5% 0% 12
8 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 1709 3% 0% 7
9 NEURAL COMPUTING & APPLICATIONS 1482 2% 0% 5
10 JOURNAL OF VLSI SIGNAL PROCESSING 1113 0% 1% 1

Author Key Words


Rank Term Chi square Shr. of publ. in
class containing
term		 Class's shr. of
term's tot. occurrences		 #P with
term in
class		 LCSH search Wikipedia search
1 CONTINUOUS ATTRACTORS 686423 4% 62% 8 Search CONTINUOUS+ATTRACTORS Search CONTINUOUS+ATTRACTORS
2 HAMMING MAXNET 418293 1% 100% 3 Search HAMMING+MAXNET Search HAMMING+MAXNET
3 K WINNER MACHINE 418293 1% 100% 3 Search K+WINNER+MACHINE Search K+WINNER+MACHINE
4 K WINNERS TAKE ALL 371813 2% 67% 4 Search K+WINNERS+TAKE+ALL Search K+WINNERS+TAKE+ALL
5 WINNER TAKE ALL 350367 8% 15% 17 Search WINNER+TAKE+ALL Search WINNER+TAKE+ALL
6 BACKGROUND NEURAL NETWORKS 278862 1% 100% 2 Search BACKGROUND+NEURAL+NETWORKS Search BACKGROUND+NEURAL+NETWORKS
7 CONTINUOUS TIME HOPFIELD NETWORK 278862 1% 100% 2 Search CONTINUOUS+TIME+HOPFIELD+NETWORK Search CONTINUOUS+TIME+HOPFIELD+NETWORK
8 DYNAMIC SHIFT 278862 1% 100% 2 Search DYNAMIC+SHIFT Search DYNAMIC+SHIFT
9 KWTA 278862 1% 100% 2 Search KWTA Search KWTA
10 LARGE GAIN BEHAVIOR 278862 1% 100% 2 Search LARGE+GAIN+BEHAVIOR Search LARGE+GAIN+BEHAVIOR

Core articles
The table includes core articles in the class. The following variables is taken into account for the relevance score of an article in a cluster c:
(1) Number of references referring to publications in the class.
(2) Share of total number of active references referring to publications in the class.
(3) Age of the article. New articles get higher score than old articles.
(4) Citation rate, normalized to year.


Rank Reference # ref.
in cl.		 Shr. of ref. in
cl.		 Citations
1 ZHENG, BC , (2014) A WINNER-TAKE-ALL LOTKA-VOLTERRA RECURRENT NEURAL NETWORK WITH ONLY ONE WINNER IN EACH ROW AND EACH COLUMN.NEURAL COMPUTING & APPLICATIONS. VOL. 24. ISSUE 7-8. P. 1749-1757 13 81% 0
2 ZHOU, W , ZURADA, JM , (2012) A COMPETITIVE LAYER MODEL FOR CELLULAR NEURAL NETWORKS.NEURAL NETWORKS. VOL. 33. ISSUE . P. 216 -227 13 68% 1
3 KOUTROUMBAS, K , (2005) COMAX: A COOPERATIVE METHOD FOR DETERMINING THE POSITION OF THE MAXIMA.NEURAL PROCESSING LETTERS. VOL. 22. ISSUE 2. P. 205-221 11 92% 0
4 KOUTROUMBAS, K , (2004) RECURRENT ALGORITHMS FOR SELECTING THE MAXIMUM INPUT.NEURAL PROCESSING LETTERS. VOL. 20. ISSUE 3. P. 179-197 10 100% 0
5 WANG, J , (2010) ANALYSIS AND DESIGN OF A K-WINNERS-TAKE-ALL MODEL WITH A SINGLE STATE VARIABLE AND THE HEAVISIDE STEP ACTIVATION FUNCTION.IEEE TRANSACTIONS ON NEURAL NETWORKS. VOL. 21. ISSUE 9. P. 1496 -1506 16 48% 27
6 SUM, J , XIAO, Y , FENG, RB , LEUNG, CS , (2015) PROPERTIES AND PERFORMANCE OF IMPERFECT DUAL NEURAL NETWORK-BASED KWTA NETWORKS.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS. VOL. 26. ISSUE 9. P. 2188 -2193 10 71% 0
7 ZHOU, W , ZURADA, JM , (2010) COMPETITIVE LAYER MODEL OF DISCRETE-TIME RECURRENT NEURAL NETWORKS WITH LT NEURONS.NEURAL COMPUTATION. VOL. 22. ISSUE 8. P. 2137-2160 12 67% 1
8 YI, Z , (2010) FOUNDATIONS OF IMPLEMENTING THE COMPETITIVE LAYER MODEL BY LOTKA-VOLTERRA RECURRENT NEURAL NETWORKS.IEEE TRANSACTIONS ON NEURAL NETWORKS. VOL. 21. ISSUE 3. P. 494-507 14 54% 17
9 CHEN, CM , HSU, MH , WANG, TY , (2002) A FAST WINNER-TAKE-ALL NEURAL NETWORKS WITH THE DYNAMIC RATIO.JOURNAL OF INFORMATION SCIENCE AND ENGINEERING. VOL. 18. ISSUE 2. P. 211 -222 13 72% 3
10 TANG, HJ , TAN, KC , ZHANG, WN , (2005) ANALYSIS OF CYCLIC DYNAMICS FOR NETWORKS OF LINEAR THRESHOLD NEURONS.NEURAL COMPUTATION. VOL. 17. ISSUE 1. P. 97-114 11 73% 12

Classes with closest relation at Level 1


Rank Class id link
1 23028 FUZZY HARDWARE//FUZZY PROCESSOR//MEMBERSHIP FUNCTION GENERATOR
2 8975 PROJECTION NEURAL NETWORK//HOPFIELD NEURAL NETWORK//RECURRENT NEURAL NETWORKS
3 7990 VISION CHIP//ADDRESS EVENT REPRESENTATION AER//NEUROMORPHIC ENGINEERING
4 35420 INCREMENTAL STABILITY//CONTRACTION THEORY//REACTION DIFFUSION PDES
5 400 GLOBAL EXPONENTIAL STABILITY//TIME VARYING DELAY//COHEN GROSSBERG NEURAL NETWORKS
6 10785 ON CHIP LEARNING//IEEE TRANSACTIONS ON NEURAL NETWORKS//CONTINUOUS VALUED NUMBER SYSTEM CVNS
7 3062 ASSOCIATIVE MEMORY//HOPFIELD MODEL//BIDIRECTIONAL ASSOCIATIVE MEMORY
8 12235 CELLULAR NEURAL NETWORKS//CNN//CELLULAR NONLINEAR NETWORKS
9 6551 MEDIAN FILTER//IMPULSE NOISE//SALT AND PEPPER NOISE
10 22324 NEURON MOS//THRESHOLD LOGIC//NEURON MOS TRANSISTOR

Go to start page