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ORCIDRobert Kozma 0001
Person information
- affiliation: University of Memphis, Dept. of Mathematical Sciences, TN, USA
- affiliation: University of Massachusetts, Department of Computer Science, Amherst, MA; USA
- affiliation: University of California at Berkeley, EECS, CA, USA
- affiliation: University of Otago, Dept. of Information Science, Dunedin, New Zealand
- affiliation: Tohoku University, Department of Quantum Science and Engineering, Sendai, Japan
- affiliation: Delft University of Technology, Netherlands
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2020 – today
- 2024
[j59]Jeffery Jonathan Joshua Davis, Florian Schübeler, Robert Kozma:
Information-Theoretical Analysis of the Cycle of Creation of Knowledge and Meaning in Brains under Multiple Cognitive Modalities. Sensors 24(5): 1605 (2024)- 2023
- [j58]Phu Pham, Loan T. T. Nguyen, Ngoc Thanh Nguyen, Robert Kozma, Bay Vo
:
A hierarchical fused fuzzy deep neural network with heterogeneous network embedding for recommendation. Inf. Sci. 620: 105-124 (2023) - [j57]Jeffery Jonathan Joshua Davis, Robert Kozma, Florian Schübeler:
Analysis of Meditation vs. Sensory Engaged Brain States Using Shannon Entropy and Pearson's First Skewness Coefficient Extracted from EEG Data. Sensors 23(3): 1293 (2023) - [j56]Wenwen Ding, Juanjuan Li, Rui Qin, Robert Kozma, Fei-Yue Wang:
A New Architecture and Mechanism for Decentralized Science MetaMarkets. IEEE Trans. Syst. Man Cybern. Syst. 53(9): 5321-5330 (2023) - [c85]Jeffery Jonathan Joshua Davis, Florian Schübeler, Robert Kozma:
Brain Dynamics in Engaged and Relaxed Psychophysiological States Reflecting the Creation of Knowledge and Meaning. SMC 2023: 1341-1346 - 2022
- [j55]Weihao Tan, Robert Kozma, Devdhar Patel:
Optimization methods for improved efficiency and performance of Deep Q-Networks upon conversion to neuromorphic population platforms. Knowl. Based Syst. 241: 108257 (2022) - [j54]Wenwen Ding, Jiachen Hou, Juanjuan Li, Chao Guo, Jirong Qin, Robert Kozma, Fei-Yue Wang:
DeSci Based on Web3 and DAO: A Comprehensive Overview and Reference Model. IEEE Trans. Comput. Soc. Syst. 9(5): 1563-1573 (2022) - [c84]Robert Kozma:
Large-Scale Networks: From Intelligent Robotics to Emergency Response. SACI 2022: 11-12 - [c83]Robert Kozma, Jeffery Jonathan Joshua Davis, Florian Schübeler, Samuel S. McAfee, James W. Wheless, Detlef Heck:
Respiratory Modulation of Cortical Rhythms - Testing The Phase Transition Hypothesis. SMC 2022: 1328-1333 - 2021
- [j53]Robert Kozma, Imre J. Rudas:
Editorial to the 50th Anniversary Issue. IEEE Trans. Syst. Man Cybern. Syst. 51(1): 2-4 (2021) - [j52]Edward W. Tunstel, Manuel J. Cobo, Enrique Herrera-Viedma, Imre J. Rudas, Dimitar P. Filev, Ljiljana Trajkovic, C. L. Philip Chen, Witold Pedrycz, Michael H. Smith, Robert Kozma:
Systems Science and Engineering Research in the Context of Systems, Man, and Cybernetics: Recollection, Trends, and Future Directions. IEEE Trans. Syst. Man Cybern. Syst. 51(1): 5-21 (2021) - [c82]Weihao Tan, Devdhar Patel, Robert Kozma:
Strategy and Benchmark for Converting Deep Q-Networks to Event-Driven Spiking Neural Networks. AAAI 2021: 9816-9824 - 2020
- [j51]Hananel Hazan, Daniel J. Saunders, Darpan T. Sanghavi, Hava T. Siegelmann, Robert Kozma:
Lattice map spiking neural networks (LM-SNNs) for clustering and classifying image data. Ann. Math. Artif. Intell. 88(11): 1237-1260 (2020) - [j50]Robert Kozma:
Editorial. IEEE Trans. Syst. Man Cybern. Syst. 50(6): 1998 (2020) - [c81]Jingyang Lu, Chenggang Yu, Erik Blasch, Roman Ilin, Hua-mei Chen, Dan Shen, Nichole Sullivan, Genshe Chen, Robert Kozma:
Deep Learning Based Domain Adaptation with Data Fusion for Aerial Image Data Analysis. ICPR Workshops (8) 2020: 118-133 - [c80]Devdhar Patel, Robert Kozma:
Unsupervised Features Extracted using Winner-Take-All Mechanism Lead to Robust Image Classification. IJCNN 2020: 1-7 - [c79]Daniel J. Saunders, Cooper Sigrist, Kenneth Chaney, Robert Kozma, Hava T. Siegelmann:
Minibatch Processing for Speed-up and Scalability of Spiking Neural Network Simulation. IJCNN 2020: 1-8 - [c78]Jeffery Jonathan Davis, Florian Schübeler, Sungchul Ji, Robert Kozma:
Discrimination Between Brain Cognitive States Using Shannon Entropy and Skewness Information Measure. SMC 2020: 4026-4031 - [i12]Stephen Chung, Robert Kozma:
Reinforcement Learning with Feedback-modulated TD-STDP. CoRR abs/2008.13044 (2020) - [i11]Weihao Tan, Devdhar Patel, Robert Kozma:
Strategy and Benchmark for Converting Deep Q-Networks to Event-Driven Spiking Neural Networks. CoRR abs/2009.14456 (2020)
2010 – 2019
- 2019
- [j49]Svante Janson, Robert Kozma, Miklós Ruszinkó, Yury Sokolov:
A modified bootstrap percolation on a random graph coupled with a lattice. Discret. Appl. Math. 258: 152-165 (2019) - [j48]Daniel J. Saunders, Devdhar Patel, Hananel Hazan, Hava T. Siegelmann, Robert Kozma:
Locally connected spiking neural networks for unsupervised feature learning. Neural Networks 119: 332-340 (2019) - [j47]Devdhar Patel, Hananel Hazan, Daniel J. Saunders, Hava T. Siegelmann, Robert Kozma:
Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to Atari Breakout game. Neural Networks 120: 108-115 (2019) - [c77]Jeffery Jonathan Joshua Davis, Robert Kozma:
Interpretation of Mesoscopic Neurodynamics by Simulating Conversion Between Pulses and Waves. IJCNN 2019: 1-8 - [c76]Robert Kozma, Raymond Noack, Hava T. Siegelmann:
Models of Situated Intelligence Inspired by the Energy Management of Brains. SMC 2019: 567-572 - [r4]Jeffery Jonathan Joshua Davis, Robert Kozma:
Movie-Making of Spatiotemporal Dynamics in Complex Systems. Encyclopedia of Computer Graphics and Games 2019 - [r3]Jeffery Jonathan Joshua Davis, Robert Kozma, Florian Schübeler:
Stress Reduction, Relaxation, and Meditative States Using Psychophysiological Measurements Based on Biofeedback Systems via HRV and EEG. Encyclopedia of Computer Graphics and Games 2019 - [i10]Devdhar Patel, Hananel Hazan, Daniel J. Saunders, Hava T. Siegelmann, Robert Kozma:
Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to ATARI games. CoRR abs/1903.11012 (2019) - [i9]Daniel J. Saunders, Devdhar Patel, Hananel Hazan, Hava T. Siegelmann, Robert Kozma:
Locally Connected Spiking Neural Networks for Unsupervised Feature Learning. CoRR abs/1904.06269 (2019) - [i8]Hananel Hazan, Daniel J. Saunders, Darpan T. Sanghavi, Hava T. Siegelmann, Robert Kozma:
Lattice Map Spiking Neural Networks (LM-SNNs) for Clustering and Classifying Image Data. CoRR abs/1906.11826 (2019) - [i7]Daniel J. Saunders, Cooper Sigrist, Kenneth Chaney, Robert Kozma, Hava T. Siegelmann:
Minibatch Processing in Spiking Neural Networks. CoRR abs/1909.02549 (2019) - [i6]Sneha Aenugu, Abhishek Sharma, Sasikiran Yelamarthi, Hananel Hazan, Philip S. Thomas, Robert Kozma:
Reinforcement learning with spiking coagents. CoRR abs/1910.06489 (2019) - 2018
- [j46]Hananel Hazan, Daniel J. Saunders, Hassaan Khan, Devdhar Patel, Darpan T. Sanghavi, Hava T. Siegelmann, Robert Kozma:
BindsNET: A Machine Learning-Oriented Spiking Neural Networks Library in Python. Frontiers Neuroinformatics 12: 89 (2018) - [c75]Gabriel P. Andrade, Miklós Ruszinkó, Robert Kozma:
Graph Models of Neurodynamics to Support Oscillatory Associative Memories. IJCNN 2018: 1-8 - [c74]Hananel Hazan, Daniel J. Saunders, Darpan T. Sanghavi, Hava T. Siegelmann, Robert Kozma:
Unsupervised Learning with Self-Organizing Spiking Neural Networks. IJCNN 2018: 1-6 - [c73]Daniel J. Saunders, Hava T. Siegelmann, Robert Kozma, Miklós Ruszinkó:
STDP Learning of Image Patches with Convolutional Spiking Neural Networks. IJCNN 2018: 1-7 - [c72]Robert Kozma, Roman Ilin, Hava T. Siegelmann:
Evolution of Abstraction Across Layers in Deep Learning Neural Networks. INNS Conference on Big Data 2018: 203-213 - [c71]Jeffery Jonathan Joshua Davis, Robert Kozma:
Visualization of Human Cognitive States Monitored by High-density EEG Arrays. INNS Conference on Big Data 2018: 219-231 - [c70]Robert Kozma, Raymond Noack, Chetan Manjesh:
Neuroenergetics of Brain Operation and Implications for Energy-Aware Computing. SMC 2018: 722-727 - [i5]Hananel Hazan, Daniel J. Saunders, Hassaan Khan, Darpan T. Sanghavi, Hava T. Siegelmann, Robert Kozma:
BindsNET: A machine learning-oriented spiking neural networks library in Python. CoRR abs/1806.01423 (2018) - [i4]Hananel Hazan, Daniel J. Saunders, Darpan T. Sanghavi, Hava T. Siegelmann, Robert Kozma:
Unsupervised Learning with Self-Organizing Spiking Neural Networks. CoRR abs/1807.09374 (2018) - [i3]Daniel J. Saunders, Hava T. Siegelmann, Robert Kozma, Miklós Ruszinkó:
STDP Learning of Image Patches with Convolutional Spiking Neural Networks. CoRR abs/1808.08173 (2018) - 2017
- [j45]Jeffrey Jonathan (Joshua) Davis, Chin-Teng Lin, Grant Gillett, Robert Kozma:
An Integrative Approach to Analyze Eeg Signals and Human Brain Dynamics in Different Cognitive States. J. Artif. Intell. Soft Comput. Res. 7(4): 287 (2017) - [j44]Minho Lee, Steven L. Bressler, Robert Kozma:
Advances in Cognitive Engineering Using Neural Networks. Neural Networks 92: 1-2 (2017) - [c69]Robert Kozma:
A cognitively motivated algorithm for rapid response in emergency situations. CogSIMA 2017: 1-4 - [c68]Raymond Noack, Chetan Manjesh, Miklós Ruszinkó, Hava T. Siegelmann, Robert Kozma:
Resting state neural networks and energy metabolism. IJCNN 2017: 228-235 - [c67]Roman Ilin, Thomas Watson, Robert Kozma:
Abstraction hierarchy in deep learning neural networks. IJCNN 2017: 768-774 - [c66]Jeffery Jonathan Joshua Davis, Robert Kozma:
Amplitude-phase relationship of brain dynamics viewed by ECoG using FIR-based Hilbert analysis. SSCI 2017: 1-8 - [c65]Raymond Noack, Jeffery Jonathan Joshua Davis, Chetan Manjesh, Robert Kozma:
Neuro-energetic aspects of cognition - The role of pulse-wave-pulse conversion in the interpretation of brain imaging data. SSCI 2017: 1-8 - 2016
- [j43]Robert Kozma, Marko Puljic:
Pattern-based computing via sequential phase transitions in hierarchical mean field neuropercolation. Theor. Comput. Sci. 633: 54-70 (2016) - [j42]Sanqing Hu, Hui Wang, Jianhai Zhang, Wanzeng Kong, Yu Cao, Robert Kozma:
Comparison Analysis: Granger Causality and New Causality and Their Applications to Motor Imagery. IEEE Trans. Neural Networks Learn. Syst. 27(7): 1429-1444 (2016) - [c64]Jeffery Jonathan Davis, Robert Kozma, Chin-Teng Lin, Walter J. Freeman:
Spatio-temporal EEG pattern extraction using high-density scalp arrays. IJCNN 2016: 889-896 - [c63]Catalina Elzo, Pablo A. Estévez, Robert Kozma:
Modeling quasi-periodic lightcurves using neuropercolation. IJCNN 2016: 2023-2030 - [c62]Jianhai Zhang, Ming Chen, Sanqing Hu, Yu Cao, Robert Kozma:
PNN for EEG-based Emotion Recognition. SMC 2016: 2319-2323 - [c61]Robert Kozma, Yury Sokolov, Marko Puljic, Sanqing Hu, Miklós Ruszinkó:
Modeling learning and strategy formation as phase transitions in cortical networks. SMC 2016: 4099-4105 - [c60]Robert Kozma:
Mass action in brains and computers - a tribute to Walter J. Freeman. SMC 2016: 4440-4443 - 2015
- [j41]Yury Sokolov, Robert Kozma, Ludmilla D. Werbos, Paul J. Werbos:
Complete stability analysis of a heuristic approximate dynamic programming control design. Autom. 59: 9-18 (2015) - [c59]Jeffery Jonathan Joshua Davis, Robert Kozma, Walter J. Freeman:
The Art of Encephalography to Understand and Discriminate Higher Cognitive Functions Visualizing Big Data on Brain Imaging Using Brain Dynamics Movies. INNS Conference on Big Data 2015: 56-63 - [p1]Robert Kozma, Jun Wang, Zhigang Zeng:
Neurodynamics. Handbook of Computational Intelligence 2015: 607-648 - 2014
- [c58]Jayanta K. Dutta, Bonny Banerjee, Roman Ilin, Robert Kozma:
Abnormal event detection in EEG imaging - Comparing predictive and model-based approaches. CIBCI 2014: 10-15 - [c57]Jeffery Jonathan Davis, Robert Kozma:
Sensitivity analysis of Hilbert transform with band-pass FIR filters for robust brain computer interface. CIBCI 2014: 16-23 - [c56]Mark H. Myers, Robert Kozma, Jeffery Jonathan Davis, Roman Ilin:
Phase cone detection optimization in EEG data. IJCNN 2014: 2504-2511 - [c55]Yury Sokolov, Robert Kozma:
Stability of dynamic brain models in neuropercolation approximation. SMC 2014: 2230-2233 - [r2]Robert Kozma:
Neural Mass Action. Encyclopedia of Computational Neuroscience 2014 - [r1]Robert Kozma:
Neuropercolation and Neural Population Models. Encyclopedia of Computational Neuroscience 2014 - 2013
- [j40]Robert Kozma, Marko Puljic:
Learning Effects in Coupled Arrays of Cellular Neural Oscillators. Cogn. Comput. 5(2): 164-169 (2013) - [j39]Muhammad M. R. Khan, Khan M. Iftekharuddin, Ernest McCracken, Khandakar Islam, Sushil Bhurtel, Lan Wang, Robert Kozma:
Autonomous wireless radar sensor mote for target material classification. Digit. Signal Process. 23(3): 722-735 (2013) - [j38]Robert Kozma, Marko Puljic:
Hierarchical random cellular neural networks for system-level brain-like signal processing. Neural Networks 45: 101-110 (2013) - [c54]Jeffery Jonathan Davis, Robert Kozma:
Creation of knowledge & meaning manifested via cortical singularities in cognition: Towards a methodology to understand intentionality and critical behavior in neural correlates of awareness. CCMB 2013: 15-22 - [c53]Yury Sokolov, Robert Kozma:
Improved stability criteria of ADP control for efficient context-aware decision support systems. iCAST/UMEDIA 2013: 41-47 - [c52]Jeffery Jonathan Joshua Davis, Robert Kozma, Walter J. Freeman:
Neurophysiological evidence of the cognitive cycle and the emergence of awareness. iCAST/UMEDIA 2013: 149-157 - [c51]Roman Ilin, Robert Kozma:
Detection of spatiotemporal phase patterns in ECoG using adaptive mixture models. IJCNN 2013: 1-7 - [c50]Robert Kozma:
The race to new mathematics of brains and consciousness - A tribute to John G. Taylor. IJCNN 2013: 1-3 - [c49]Robert Kozma, João Luís Garcia Rosa, Denis Renato de Moraes Piazentin:
Cognitive clustering algorithm for efficient cybersecurity applications. IJCNN 2013: 1-8 - [c48]Mark H. Myers, Charlotte A. Joure, Carley Johnston, Aaron Canales, Akshay Padmanabha, Robert Kozma:
Spatial alignment of scalp EEG activity during cognitive tasks. IJCNN 2013: 1-8 - [i2]Yury Sokolov, Robert Kozma, Ludmilla Werbos, Paul J. Werbos:
Complete stability analysis of a heuristic ADP control design. CoRR abs/1308.3282 (2013) - 2012
- [j37]Ludmilla Werbos, Robert Kozma, Rodrigo Silva-Lugo, Giovanni Egidio Pazienza, Paul J. Werbos:
Metamodeling and the Critic-based approach to multi-level optimization. Neural Networks 32: 179-185 (2012) - [j36]Robert Kozma, Lan Wang, Khan M. Iftekharuddin, Ernest McCracken, Muhammad M. R. Khan, Khandakar Islam, Sushil Bhurtel, Rustu Murat Demirer:
A Radar-Enabled Collaborative Sensor Network Integrating COTS Technology for Surveillance and Tracking. Sensors 12(2): 1336-1351 (2012) - [c47]Gahangir Hossain, Mark H. Myers, Robert Kozma:
Study of Phase Relationships in ECoG Signals Using Hilbert-Huang Transforms. BICS 2012: 174-182 - [c46]Robert Kozma, Jeffery Jonathan Davis:
On the invariance of cortical synchronization measures across a broad range of frequencies. iCAST 2012: 280-285 - [c45]Germano Resconi, Robert Kozma:
Geometric Syncronisation by Multi-pendulum and Electronic Models of Neurodynamics. IJCCI (Selected Papers) 2012: 247-261 - [c44]Germano Resconi, Robert Kozma:
Geometric Image of Neurodynamics. IJCCI 2012: 457-465 - [c43]Jeffery Jonathan Davis, Robert Kozma:
Analysis of phase relationship in ECoG using Hilbert transform and information theoretic measures. IJCNN 2012: 1-7 - [c42]Walter J. Freeman, Robert Kozma, Giuseppe Vitiello:
Adaptation of the generalized Carnot cycle to describe thermodynamics of cerebral cortex. IJCNN 2012: 1-8 - [c41]Roman Ilin, Robert Kozma:
Cognitively motivated learning of categorical data with Modeling Fields Theory. IJCNN 2012: 1-8 - 2011
- [c40]Robert Kozma:
Neural correlates of awareness in brains and in man-made devices. iCAST 2011: 516-520 - [c39]Giovanni Egidio Pazienza, Robert Kozma, Jordi Albo-Canals:
Percolation in memristive networks. IJCNN 2011: 2761-2763 - [c38]Ludmilla Werbos, Robert Kozma, Rodrigo Silva-Lugo, Giovanni Egidio Pazienza, Paul J. Werbos:
Metamodeling for large-scale optimization tasks based on object networks. IJCNN 2011: 2905-2910 - [c37]Mark H. Myers, Robert Kozma:
Modeling normal/epileptic brain dynamics with potential application in titration therapy. IJCNN 2011: 3085-3092 - [c36]Giovanni Egidio Pazienza, Robert Kozma:
Memristor as an archetype of dynamic data-driven systems and applications to sensor networks. ICCS 2011: 1782-1787 - 2010
- [j35]Marko Puljic, Robert Kozma:
Broad-band Oscillations by Probabilistic Cellular Automata. J. Cell. Autom. 5(6): 491-507 (2010) - [j34]Walter J. Freeman, Robert Kozma:
Freeman's mass action. Scholarpedia 5(1): 8040 (2010) - [c35]Robert Kozma, Marko Puljic:
Chaotic behavior in probabilistic cellular neural networks. IJCNN 2010: 1-7
2000 – 2009
- 2009
- [j33]Robert Kozma:
2009 International Joint Conference on Neural Networks (IJCNN 2009) [Conference Reports]. IEEE Comput. Intell. Mag. 4(4): 18-20 (2009) - [j32]Robert Kozma, Daniel S. Levine, Leonid I. Perlovsky:
Introduction to the special issue on goal-directed neural systems. Neural Networks 22(3): 197-199 (2009) - [j31]Robert Kozma, Walter J. Freeman:
The KIV model of intentional dynamics and decision making. Neural Networks 22(3): 277-285 (2009) - [j30]Robert Kozma, Steven L. Bressler, Leonid I. Perlovsky, Ganesh K. Venayagamoorthy:
Advances in neural networks research: An introduction. Neural Networks 22(5-6): 489-490 (2009) - [c34]Rustu Murat Demirer, Robert Kozma, Mert Çaglar, Yasar Polatoglu:
A new nonlinear filter design for the detection of phase transitions in ECoG data. IJCNN 2009: 671-676 - [c33]Roman Ilin, Robert Kozma:
Sensor integration in KIV brain model for decision making. IJCNN 2009: 1328-1334 - [c32]Mark H. Myers, Robert Kozma:
Seizure prediction through dynamic synchronization measures of neural populations. IJCNN 2009: 2195-2201 - [c31]Robert Kozma, Walter J. Freeman:
Neurodynamics of cognition and consciousness. PerMIS 2009: 147-148 - 2008
- [j29]Robert Kozma, Terry Huntsberger, Hrand Aghazarian, Edward W. Tunstel, Roman Ilin, Walter J. Freeman:
Intentional Control for Planetary Rover SRR. Adv. Robotics 22(12): 1309-1327 (2008) - [j28]Roman Ilin, Robert Kozma, Paul J. Werbos:
Beyond Feedforward Models Trained by Backpropagation: A Practical Training Tool for a More Efficient Universal Approximator. IEEE Trans. Neural Networks 19(6): 929-937 (2008) - [c30]Hima B. Puppala, Robert Kozma:
Identification of phase transitions in simulated EEG signals. IJCNN 2008: 3511-3517 - [c29]Robert Kozma, Leonid I. Perlovsky, JaiSantosh Ankishetty:
Detection of propagating phase gradients in EEG signals using Model Field Theory of non-Gaussian mixtures. IJCNN 2008: 3524-3529 - 2007
- [j27]Robert Kozma, Hrand Aghazarian, Terry Huntsberger, Eddie Tunstel, Walter J. Freeman:
Computational Aspects of Cognition and Consciousness in Intelligent Devices. IEEE Comput. Intell. Mag. 2(3): 53-64 (2007) - [j26]Igor Beliaev, Robert Kozma:
Time series prediction using chaotic neural networks on the CATS benchmark. Neurocomputing 70(13-15): 2426-2439 (2007) - [j25]Robert Kozma:
Neuropercolation. Scholarpedia 2(8): 1360 (2007) - [c28]Roman Ilin, Robert Kozma:
Control of multi-stable chaotic neural networks using input constraints. IJCNN 2007: 2194-2199 - [c27]Robert Kozma, Ross W. Deming, Leonid I. Perlovsky:
Estimation of Propagating Phase Transients in EEG Data - Application of Dynamic Logic Neural Modeling Approach. IJCNN 2007: 2341-2345 - [c26]Robert Linnehan, John Schindler, David Brady, Robert Kozma, Ross W. Deming, Leonid I. Perlovsky:
Resolving Wall Ambiguities Using Angular Diverse Synthetic Arrays. IJCNN 2007: 2758-2763 - [c25]Robert Kozma, Terry Huntsberger, Hrand Aghazarian, Walter J. Freeman:
Implementing intentional robotics principles using SSR2K platform. IROS 2007: 2262-2267 - [i1]Roman Ilin, Robert Kozma, Paul J. Werbos:
Beyond Feedforward Models Trained by Backpropagation: a Practical Training Tool for a More Efficient Universal Approximator. CoRR abs/0710.4182 (2007) - 2006
- [j24]Robert Kozma, Toshio Fukuda:
Intentional dynamic systems: Fundamental concepts and applications. Int. J. Intell. Syst. 21(9): 875-879 (2006) - [j23]Derek Harter, Robert Kozma:
Aperiodic dynamics and the self-organization of cognitive maps in autonomous agents. Int. J. Intell. Syst. 21(9): 955-971 (2006) - [j22]Paul N. Balister, Béla Bollobás, Robert Kozma:
Large deviations for mean field models of probabilistic cellular automata. Random Struct. Algorithms 29(3): 399-415 (2006) - [c24]Robert Kozma, Anna L. Buczak:
Biomedical Hypothesis Generation and Testing by Evolutionary Computation. DMIN 2006: 97-106 - [c23]Roman Ilin, Robert Kozma, Paul J. Werbos:
Cellular SRN Trained by Extended Kalman Filter Shows Promise for ADP. IJCNN 2006: 506-510 - [c22]Robert Kozma:
Influence of Criticality on 1/falphaSpectral Characteristics of Cortical Neuron Populations. IJCNN 2006: 632-637 - [c21]Igor Beliaev, Robert Kozma:
Studies on the Memory Capacity and Robustness of Chaotic Dynamic Neural Networks. IJCNN 2006: 3991-3998 - [c20]Kausik Kumar Majumdar, Robert Kozma:
Studies on Sparse Array Cortical Modeling and Memory Cognition Duality. IJCNN 2006: 4954-4957 - 2005
- [j21]Robert Kozma, Marko Puljic, Paul Balister, Béla Bollobás, Walter J. Freeman:
Phase transitions in the neuropercolation model of neural populations with mixed local and non-local interactions. Biol. Cybern. 92(6): 367-379 (2005) - [j20]Marko Puljic, Robert Kozma:
Activation clustering in neural and social networks. Complex. 10(4): 42-50 (2005) - [j19]Robert Kozma, Derek Wong, Rustu Murat Demirer, Walter J. Freeman:
Learning intentional behavior in the K-model of the amygdala and entorhinal cortex with the cortico-hyppocampal formation. Neurocomputing 65-66: 23-30 (2005) - [j18]Derek Harter, Robert Kozma:
Chaotic neurodynamics for autonomous agents. IEEE Trans. Neural Networks 16(3): 565-579 (2005) - [c19]Robert Kozma, Edward W. Tunstel:
A Novel Approach to Distributed Sensory Networks Using Biologically-Inspired Sensory Fusion. SMC 2005: 1005-1010 - [c18]Igor Beliaev, Roman Ilin, Robert Kozma:
Nonlinear Neurodynamics Tool for System Analysis and Application for Time Series Prediction. SMC 2005: 1011-1016 - 2004
- [j17]Horatiu Voicu, Robert Kozma, Derek Wong, Walter J. Freeman:
Spatial navigation model based on chaotic attractor networks. Connect. Sci. 16(1): 1-19 (2004) - [j16]Robert Kozma, Walter J. Freeman, Derek Wong, Péter Érdi:
Learning environmental clues in the KIV model of the cortico-hippocampal formation. Neurocomputing 58-60: 721-728 (2004) - [j15]Deliang Wang, Walter J. Freeman, Robert Kozma, Andrzej Lozowski, Ali A. Minai:
Guest Editorial Special Issue on Temporal Coding for Neural Information Processing. IEEE Trans. Neural Networks 15(5): 953-956 (2004) - [c17]Robert Kozma, Marko Puljic, Paul Balister, Béla Bollobás, Walter J. Freeman:
Neuropercolation: A Random Cellular Automata Approach to Spatio-temporal Neurodynamics. ACRI 2004: 435-443 - [c16]Derek Harter, Robert Kozma:
Aperiodic Dynamics and the Self-Organization of Cognitive Maps in Autonomous Agents. FLAIRS 2004: 424-429 - [c15]Derek Wong, Robert Kozma, Edward W. Tunstel, Walter J. Freeman:
Navigation in a Challenging Martian Environment using Multi-sensory Fusion in KIV Model. ICRA 2004: 672-677 - [c14]Derek Harter, Robert Kozma:
Aperiodic Dynamics for Appetitive/aversive Behavior in Autonomous Agents. ICRA 2004: 2147-2152 - [c13]Robert Kozma, Sangeeta Muthu:
Implementing reinforcement learning in the chaotic KIV model using mobile robot AIBO. IROS 2004: 2337-2342 - 2003
- [j14]Robert Kozma, Walter J. Freeman, Péter Érdi:
The KIV model - nonlinear spatio-temporal dynamics of the primordial vertebrate forebrain. Neurocomputing 52-54: 819-826 (2003) - [c12]Robert Kozma, Horatiu Voicu, Derek Wong, Walter J. Freeman:
Dynamical neural network algorithm for autonomous learning and navigation control. SMC 2003: 2132-2137 - 2002
- [j13]Robert Kozma, Walter J. Freeman:
Classification of EEG patterns using nonlinear dynamics and identifying chaotic phase transitions. Neurocomputing 44-46: 1107-1112 (2002) - [j12]Prasun K. Roy, Robert Kozma, D. Dutta Majumder:
From neurocomputation to immunocomputation - a model and algorithm for fluctuation-induced instability and phase transition in biological systems. IEEE Trans. Evol. Comput. 6(3): 292-305 (2002) - [c11]Fabio A. González, Dipankar Dasgupta, Robert Kozma:
Combining negative selection and classification techniques for anomaly detection. IEEE Congress on Evolutionary Computation 2002: 705-710 - [c10]Max H. Garzon, Prashant Ankaraju, Evan M. Drumwright, Robert Kozma:
Neurofuzzy recognition and generation of facial features in talking heads. FUZZ-IEEE 2002: 926-931 - 2001
- [j11]Robert Kozma, Walter J. Freeman:
Chaotic Resonance - Methods and Applications for Robust Classification of noisy and Variable Patterns. Int. J. Bifurc. Chaos 11(6): 1607-1630 (2001) - [j10]Robert Kozma, Maritza Alvarado, Linda J. Rogers, Brian Lau, Walter J. Freeman:
Emergence of un-correlated common-mode oscillations in the sensory cortex. Neurocomputing 38-40: 747-755 (2001) - [j9]Nikola K. Kasabov, Jaesoo Kim, Robert Kozma, Tico Cohen:
Rule Extraction from Fuzzy Neural Networks FuNN: A Method and a Real-World Application. J. Adv. Comput. Intell. Intell. Informatics 5(4): 193-200 (2001) - [c9]Robert Kozma, Walter J. Freeman:
Control of mesoscopic/intermediate-range spatio-temporal chaos in the cortex. ACC 2001: 263-268 - [c8]Derek Harter, Robert Kozma:
Task Environments for the Dynamic Development of Behavior. International Conference on Computational Science (2) 2001: 300-309 - 2000
- [j8]Nikola K. Kasabov, Robert Kozma:
Methods and systems for intelligent human-computer interaction. Inf. Sci. 123(1-2): 1-2 (2000) - [c7]Robert Kozma, Walter J. Freeman:
Encoding and Recall of Noisy Data as Chaotic Spatio-Temporal Memory Patterns in the Style of the Brains. IJCNN (5) 2000: 33-38
1990 – 1999
- 1999
- [c6]Robert Kozma, Walter J. Freeman:
A possible mechanism for intermittent oscillations in the KIII model of dynamic memories - the case study of olfaction. IJCNN 1999: 52-57 - 1998
- [j7]Nikola K. Kasabov, Robert Kozma:
Introduction: Hybrid intelligent adaptive systems. Int. J. Intell. Syst. 13(6): 453-454 (1998) - [j6]Nikola K. Kasabov, Robert Kozma:
Hybrid intelligent adaptive systems: A framework and a case study on speech recognition. Int. J. Intell. Syst. 13(6): 455-466 (1998) - [j5]Robert Kozma, Nikola K. Kasabov, Jaesoo Kim, Tico Cohen:
Integration of connectionist methods and chaotic time-series analysis for the prediction of process data. Int. J. Intell. Syst. 13(6): 519-538 (1998) - [j4]Nikola K. Kasabov, Robert Kozma, Michael J. Watts:
Phoneme-Based Speech Recognition via Fuzzy Neural Networks Modeling and Learning. Inf. Sci. 110(1-2): 61-79 (1998) - [j3]Nikola K. Kasabov, Robert Kozma:
Editorial: Self-Organization and Adaptation in Intelligent Systems. J. Adv. Comput. Intell. Intell. Informatics 2(6): 177 (1998) - [e2]Nikola K. Kasabov, Robert Kozma, Kitty Ko, Robert O'Shea, George G. Coghill, Tom Gedeon:
Progress in Connectionist-Based Information Systems: Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, ICONIP 1997, Volume I, Dunedin, New Zealand, 24-28 November, 1997. Springer 1998, ISBN 0-444-88545-5 [contents] - [e1]Nikola K. Kasabov, Robert Kozma, Kitty Ko, Robert O'Shea, George G. Coghill, Tom Gedeon:
Progress in Connectionist-Based Information Systems: Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, ICONIP 1997, Volume II, Dunedin, New Zealand, 24-28 November, 1997. Springer 1998 [contents] - 1997
- [c5]Robert Kozma:
On the conscious and subconscious components of knowledge representation in neural networks. ICNN 1997: 2519-2523 - [c4]Robert Kozma, J. A. Swope, Nikola K. Kasabov, M. J. A. Williams:
Multi-Agent Implementation of Fractal Analysis by Fuzzy Neural Networks. ICONIP (1) 1997: 162-165 - [c3]Nikola K. Kasabov, Robert Kozma, Richard Kilgour, Mark R. Laws, J. Taylor, Michael J. Watts, Andrew R. Gray:
A Methodology for Speech Data Analysis and a Framework for Adaptive Speech Recognition Using Fuzzy Neural Networks. ICONIP (2) 1997: 1055-1060 - 1996
- [j2]Robert Kozma, Masatake Sakuma, Yoichi Yokoyama, Masaharu Kitamura:
On the accuracy of mapping by neural networks trained by backpropagation with forgetting. Neurocomputing 13(2-4): 295-311 (1996) - 1995
- [j1]Robert Kozma, Masatake Sakuma, S. Sato, Masaharu Kitamura:
An Adaptive Neuro-Fuzzy Signal Processing Method By Using Structural Learning with Forgetting. Intell. Autom. Soft Comput. 1(4): 389-404 (1995) - [c2]Robert Kozma, Masaharu Kitamura, Aleksander Malinowski, Jacek M. Zurada:
On Performance Measures of Artificial Neural Networks Trained by Structural Learning with Forgetting. ANNES 1995: 22-25 - [c1]Robert Kozma, Masaharu Kitamura:
Dynamic structure adaptation in feedforward neural networks-an example of plant monitoring. ICNN 1995: 692-697
Coauthor Index
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