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Research Zernike (ZIAM) Bio-inspired Circuits & Systems Chicca group

Publications

2024

Gibertini, P., Fehlings, L., Mikolajick, T., Chicca, E., Kappel, D., & Covi, E. (2024). Coincidence Detection with an Analog Spiking Neuron Exploiting Ferroelectric Polarization. In ISCAS 2024 - IEEE International Symposium on Circuits and Systems (Proceedings - IEEE International Symposium on Circuits and Systems). IEEE. https://doi.org/10.1109/ISCAS58744.2024.10558196
Quintana, F. M., Perez-Peña, F., Galindo, P. L., Neftci, E. O., Chicca, E., & Khacef, L. (2024). ETLP: event-based three-factor local plasticity for online learning with neuromorphic hardware. Neuromorphic computing and engineering, 4(3), Article 034006. https://doi.org/10.1088/2634-4386/ad6733
Schoepe, T., Janotte, E., Milde, M. B., Bertrand, O. J. N., Egelhaaf, M., & Chicca, E. (2024). Finding the gap: Neuromorphic motion-vision in dense environments. Nature Communications, 15(1), Article 817. https://doi.org/10.1038/s41467-024-45063-y
Schoepe, T., Drix, D., Schüffny, F. M., Miko, R., Sutton, S., Chicca, E., & Schmuker, M. (2024). Odour Localization in Neuromorphic Systems. In 2024 IEEE International Symposium on Circuits and Systems (ISCAS) (Proceedings - IEEE International Symposium on Circuits and Systems). IEEE. https://doi.org/10.1109/ISCAS58744.2024.10558186

2023

Nilsson, M., Pina, T. J., Khacef, L., Liwicki, F., Chicca, E., & Sandin, F. (2023). A Comparison of Temporal Encoders for Neuromorphic Keyword Spotting with Few Neurons. In International Joint Conference on Neural Networks (IJCNN): Proceedings (Proceedings of the International Joint Conference on Neural Networks). IEEE. https://doi.org/10.1109/IJCNN54540.2023.10191938
Richter, O., Greatorex, H., Hučko, B., Cotteret, M., Soares Girão, W., Janotte, E., Mastella, M., & Chicca, E. (2023). A Subthreshold Second-Order Integration Circuit for Versatile Synaptic Alpha Kernel and Trace Generation. In AMC ICONS2023 (pp. 1-4). Article 33 ACM Press. https://doi.org/10.1145/3589737.3606008
Schoepe, T., Gutierrez-Galan, D., Dominguez-Morales, J. P., Greatorex, H., Jimenez-Fernandez, A., Linares-Barranco, A., & Chicca, E. (2023). Closed-loop sound source localization in neuromorphic systems. Neuromorphic computing and engineering, 3(2), Article 024009. https://doi.org/10.1088/2634-4386/acdaba
Wang, X., Risi, N., Talavera Martínez, E., Chicca, E., & Azzopardi, G. (2023). Fall detection with event-based data: A case study. In N. Tsapatsoulis (Ed.), Computer Analysis of Images and Patterns: 20th International Conference, CAIP 2023 Limassol, Cyprus, September 25–28, 2023 Proceedings, Part II (pp. 33-42). (Lecture Notes in Computer Science; Vol. 14185). Springer. https://doi.org/10.1007/978-3-031-44240-7_4
Schoepe, T., & Chicca, E. (2023). Finding the Goal: Insect-Inspired Spiking Neural Network for Heading Error Estimation. In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023 (pp. 4727-4733). (IEEE International Conference on Intelligent Robots and Systems). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IROS55552.2023.10342210
Kugele, A., Pfeil, T., Pfeiffer, M., & Chicca, E. (2023). How Many Events Make an Object? Improving Single-frame Object Detection on the 1 Mpx Dataset. In Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023 (pp. 3913-3922). (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2023-June). IEEE Computer Society. https://doi.org/10.1109/CVPRW59228.2023.00406
Bouanane, M. S., Cherifi, D., Chicca, E., & Khacef, L. (2023). Impact of spiking neurons leakages and network recurrences on event-based spatio-temporal pattern recognition. Frontiers in Neuroscience, 17, Article 1244675. https://doi.org/10.3389/fnins.2023.1244675
Cotteret, M., Richter, O., Mastella, M., Greatorex, H., Janotte, E., Soares Girão, W., Ziegler, M., & Chicca, E. (2023). Robust Spiking Attractor Networks with a Hard Winner-Take-All Neuron Circuit. In 2023 IEEE International Symposium on Circuits and Systems (ISCAS): Proceedings IEEE. https://doi.org/10.1109/ISCAS46773.2023.10181513
Khacef, L., Klein, P., Cartiglia, M., Rubino, A., Indiveri, G., & Chicca, E. (2023). Spike-based local synaptic plasticity: a survey of computational models and neuromorphic circuits. Neuromorphic computing and engineering, 3(4), Article 042001. https://doi.org/10.1088/2634-4386/ad05da
Mastella, M., Greatorex, H., Cotteret, M., Janotte, E., Soares Girão, W., Richter, O., & Chicca, E. (2023). Synaptic Normalisation for On-Chip Learning in Analog CMOS Spiking Neural Networks. In ACM ICONS2023: Proceedings of the 2023 International Conference on Neuromorphic Systems (pp. 1-4). Article 34 ACM Press. https://doi.org/10.1145/3589737.3606007

2022

Schoepe, T., Janotte, E., Milde, M. B., Bertrand, O. J. N., Egelhaaf, M., & Chicca, E. (2022). Finding the Gap: Neuromorphic Motion Vision in Cluttered Environments. Research Square Company. https://doi.org/10.21203/rs.3.rs-493274/v1
Kugele, A., Pfeil, T., Pfeiffer, M., & Chicca, E. (2022). Hybrid SNN-ANN: Energy-Efficient Classification and Object Detection for Event-Based Vision. In C. Bauckhage, J. Gall, & A. Schwing (Eds.), Pattern Recognition (pp. 297–312). (Pattern Recognition. DAGM GCPR), (Lecture Notes in Computer Science; Vol. 13024). Springer. https://doi.org/10.1007/978-3-030-92659-5_19
Cotteret, M., Greatorex, H., Ziegler, M., & Chicca, E. (2022). Vector Symbolic Finite State Machines in Attractor Neural Networks. arXiv. https://doi.org/10.48550/arXiv.2212.01196

2021

Gutierrez-Galan, D., Schoepe, T., Dominguez-Morales, J. P., Jimenez-Fernandez, A., Chicca, E., & Linares-Barranco, A. (2022). An Event-Based Digital Time Difference Encoder Model Implementation for Neuromorphic Systems. IEEE Transactions on Neural Networks and Learning Systems, 33(5), 1959-1973. https://doi.org/10.1109/TNNLS.2021.3108047
Sengupta, D., Mastella, M., Chicca, E., & Kottapalli, A. G. P. (2022). Skin-Inspired Flexible and Stretchable Electrospun Carbon Nanofiber Sensors for Neuromorphic Sensing. Acs applied electronic materials, 4(1), 308-315. https://doi.org/10.1021/acsaelm.1c01010
Mastella, M., & Chicca, E. (2021). A Hardware-friendly Neuromorphic Spiking Neural Network for Frequency Detection and Fine Texture Decoding. In 2021 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1-5). Article 9401377 IEEE. https://doi.org/10.1109/ISCAS51556.2021.9401377
Jürgensen, A. M., Khalili, A., Chicca, E., Indiveri, G., & Nawrot, M. P. (2021). A neuromorphic model of olfactory processing and sparse coding in the Drosophila larva brain. Neuromorphic computing and engineering, 1(2), Article 024008. https://doi.org/10.1088/2634-4386/ac3ba6
Dabbous, A., Mastella, M., Natarajan, A., Chicca, E., Valle, M., & Bartolozzi, C. (2021). Artificial Bio-inspired Tactile Receptive Fields for Edge Orientation Classification. In 2021 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1-5). Article 9401749 IEEE. https://doi.org/10.1109/ISCAS51556.2021.9401749
Covi, E., Duong, Q. T., Lancaster, S., Havel, V., Coignus, J., Barbot, J., Richter, O., Klein, P., Chicca, E., Grenouillet, L., Dimoulas, A., Mikolajick, T., & Slesazeck, S. (2021). Ferroelectric Tunneling Junctions for Edge Computing. In 2021 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1-5). Article 9401800 IEEE. https://doi.org/10.1109/ISCAS51556.2021.9401800
Janotte, E., Mastella, M., Chicca, E., & Bartolozzi, C. (2021). Touch in Robots: A Neuromorphic Approach. ERCIM News, Brain-Inspired Computing(125), 34-51. https://ercim-news.ercim.eu/en125/special/brain-inspired-computing-introduction-to-the-special-theme

2020

Chicca, E., & Indiveri, G. (2020). A recipe for creating ideal hybrid memristive-CMOS neuromorphic processing systems. Applied Physics Letters, 116(12), Article 120501. https://doi.org/10.1063/1.5142089
Pedretti, G., Mannocci, P., Hashemkhani, S., Milo, V., Melnic, O., Chicca, E., & Ielmini, D. (2020). A Spiking Recurrent Neural Network With Phase-Change Memory Neurons and Synapses for the Accelerated Solution of Constraint Satisfaction Problems. Ieee journal on exploratory solid-State computational devices and circuits, 6(1), 89-97. Article 9086758. https://doi.org/10.1109/JXCDC.2020.2992691
Pedretti, G., Milo, V., Hashemkhani, S., Mannocci, P., Melnic, O., Chicca, E., & Ielmini, D. (2020). A Spiking Recurrent Neural Network with Phase Change Memory Synapses for Decision Making. In 2020 IEEE International Symposium on Circuits and Systems (ISCAS) IEEE. https://doi.org/10.1109/ISCAS45731.2020.9180513
Linares-Barranco, A., Perez-Pena, F., Jimenez-Fernandez, A., & Chicca, E. (2020). ED-BioRob: A Neuromorphic Robotic Arm With FPGA-Based Infrastructure for Bio-Inspired Spiking Motor Controllers. Frontiers in neurorobotics, 14, Article 590163. https://doi.org/10.3389/fnbot.2020.590163
Kugele, A., Pfeil, T., Pfeiffer, M., & Chicca, E. (2020). Efficient Processing of Spatio-Temporal Data Streams With Spiking Neural Networks. Frontiers in Neuroscience, 14, Article 439. https://doi.org/10.3389/fnins.2020.00439
D'Angelo, G., Janotte, E., Schoepe, T., O'Keeffe, J., Milde, M. B., Chicca, E., & Bartolozzi, C. (2020). Event-Based Eccentric Motion Detection Exploiting Time Difference Encoding. Frontiers in Neuroscience, 14, Article 451. https://doi.org/10.3389/fnins.2020.00451
Schoepe, T., Gutierrez-Galan, D., Dominguez-Morales, J. P., Jimenez-Fernandez, A., Linares-Barranco, A., & Chicca, E. (2020). Live Demonstration: Neuromorphic Sensory Integration for Combining Sound Source Localization and Collision Avoidance. Abstract from 2020 IEEE International Symposium on Circuits & Systems, Seville, Spain.
Schoepe, T., Gutierrez-Galan, D., Dominguez-Morales, J. P., Jimenez-Fernandez, A., Linares-Barranco, A., & Chicca, E. (2020). Live Demonstration: Neuromorphic Sensory Integration for Combining Sound Source Localization and Collision Avoidance. In 2020 IEEE International Symposium on Circuits and Systems (ISCAS) IEEE. https://doi.org/10.1109/ISCAS45731.2020.9181257

2019

Thakur, C. S., Molin, J. L., Cauwenberghs, G., Indiveri, G., Kumar, K., Qiao, N., Schemmel, J., Wang, R., Chicca, E., Hasler, J. O., Seo, J., Yu, S., Cao, Y., van Schaik, A., & Etienne-Cummings, R. (2019). Large-Scale Neuromorphic Spiking Array Processors: A Quest to Mimic the Brain (vol 12, 891, 2018). Frontiers in Neuroscience, 12, Article 991. https://doi.org/10.3389/fnins.2018.00991
Schoepe, T., Gutierrez-Galan, D., Dominguez-Morales, J. P., Jimenez-Fernandez, A., Linares-Barranco, A., & Chicca, E. (2019). Neuromorphic Sensory Integration for Combining Sound Source Localization and Collision Avoidance. In 2019 IEEE Biomedical Circuits and Systems Conference (BioCAS) IEEE. https://doi.org/10.1109/BIOCAS.2019.8919202
Suresh, B., Bertele, M., Breyer, E. T., Klein, P., Mulaosmanovic, H., Mikolajick, T., Slesazeck, S., & Chicca, E. (2019). Simulation of integrate-and-fire neuron circuits using HfO2-based ferroelectric field effect transistors. In 2019 26th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2019 (pp. 229-232). Article 8965004 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICECS46596.2019.8965004

2018

Milo, V., Chicca, E., & Ielmini, D. (2018). Brain-Inspired Recurrent Neural Network with Plastic RRAM Synapses. In 2018 IEEE International Symposium on Circuits and Systems (ISCAS) IEEE. https://doi.org/10.1109/ISCAS.2018.8351523
Basu, A., Chang, M.-F., Chicca, E., Karnik, T., Li, H., & Seo, J.-S. (2018). Guest Editorial Low-Power, Adaptive Neuromorphic Systems: Devices, Circuit, Architectures and Algorithms. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 8(1), 1-5. https://doi.org/10.1109/JETCAS.2018.2810399
Thakur, C. S., Molin, J. L., Cauwenberghs, G., Indiveri, G., Kumar, K., Qiao, N., Schemmel, J., Wang, R., Chicca, E., Hasler, J. O., Seo, J., Yu, S., Cao, Y., van Schaik, A., & Etienne-Cummings, R. (2018). Large-Scale Neuromorphic Spiking Array Processors: A Quest to Mimic the Brain. Frontiers in Neuroscience, 12, Article 891. https://doi.org/10.3389/fnins.2018.00891
Mulaosmanovic, H., Chicca, E., Bertele, M., Mikolajick, T., & Slesazeck, S. (2018). Mimicking biological neurons with a nanoscale ferroelectric transistor. Nanoscale, 10(46), 21755-21763. https://doi.org/10.1039/c8nr07135g
Donati, E., Perez-Peña, F., Bartolozzi, C., Indiveri, G., & Chicca, E. (2018). Open-Loop Neuromorphic Controller Implemented on VLSI Devices. In 2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob) IEEE. https://doi.org/10.1109/BIOROB.2018.8487937
Milo, V., Pedretti, G., Laudato, M., Bricalli, A., Ambrosi, E., Bianchi, S., Chicca, E., & Ielmini, D. (2018). Resistive switching synapses for unsupervised learning in feed-forward and recurrent neural networks. In 2018 IEEE International Symposium on Circuits and Systems (ISCAS) IEEE. https://doi.org/10.1109/ISCAS.2018.8351824
Milde, M. B., Bertrand, O. J. N., Ramachandran, H., Egelhaaf, M., & Chicca, E. (2018). Spiking Elementary Motion Detector in Neuromorphic Systems. Neural computation, 30(9), 2384-2417. https://doi.org/10.1162/neco_a_01112
Ziegler, M., Wenger, C., Chicca, E., & Kohlstedt, H. (2018). Tutorial: Concepts for closely mimicking biological learning with memristive devices: Principles to emulate cellular forms of learning. Journal of Applied Physics, 124(15), Article 152003. https://doi.org/10.1063/1.5042040
Rüttgers, S., Klein, P., Ziegler, M., & Chicca, E. (2018). Unsupervised MNIST Learning in an analog Spiking Neural Network using digital memristive devices. Abstract from Conference in Cognitive Computing 2018 , Hannover, Germany.

2017

Milo, V., Ielmini, D., & Chicca, E. (2017). Attractor networks and associative memories with STDP learning in RRAM synapses. In 2017 IEEE International Electron Devices Meeting (IEDM) IEEE. https://doi.org/10.1109/IEDM.2017.8268369
Perez-Peña, F., Leñero-Bardallo, J. A., Linares-Barranco, A., & Chicca, E. (2017). Towards Bioinspired Close-Loop Local Motor Control: A Simulated Approach Supporting Neuromorphic Implementations. In 2017 IEEE International Symposium on Circuits and Systems (ISCAS) IEEE. https://doi.org/10.1109/ISCAS.2017.8050808

2016

Huayaney, F. L. M., & Chicca, E. (2016). A VLSI Implementation of a calcium-based plasticity learning model. In 2016 IEEE International Symposium on Circuits and Systems (ISCAS) IEEE. https://doi.org/10.1109/ISCAS.2016.7527248
Chang, J., Sonkusale, S., Yalcin, M., Ogunfunmi, T., Vanderwalle, J., Zhu, W.-P., Liu, Z., Chang, R. C.-H., Chicca, E., Callegari, S., Chu, C.-C., Dudek, P., Lee, G. G., & Chowdhury, M. (2016). Current And Emergent Topics. In F. Maloberti, & A. C. Davies (Eds.), A Short History of Circuits And Systems (pp. 255-265). River Publishers.
Mayr, C. G., Sheik, S., Bartolozzi, C., & Chicca, E. (2016). Editorial: Synaptic Plasticity for Neuromorphic Systems. Frontiers in Neuroscience, 10, Article 214. https://doi.org/10.3389/fnins.2016.00214
Biolek, D., Carrara, S., Chicca, E., Corinto, F., Georgiou, J., Linares-Barranco, B., Prodromakis, T., Spiga, S., & Tetzlaff, R. (2016). EU COST action IC1401 - Pushing the frontiers of memristive devices to systems. In 2016 18th Mediterranean Electrotechnical Conference (MELECON) IEEE. https://doi.org/10.1109/MELCON.2016.7495309
Nease, S., & Chicca, E. (2016). Floating-Gate-Based Intrinsic Plasticity with Low-Voltage Rate Control. In 2016 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 2507-2510). IEEE. https://doi.org/10.1109/ISCAS.2016.7539102
Schirmer, M., Stradolini, F., Carrara, S., & Chicca, E. (2016). FPGA-based Approach for Automatic Peak Detection in Cyclic Voltammetry. In 2016 IEEE International Conference on Electronics, Circuits and Systems (ICECS) (pp. 65-68). IEEE. https://doi.org/10.1109/ICECS.2016.7841133
Huayaney, F. L. M., Nease, S., & Chicca, E. (2016). Learning in Silicon Beyond STDP: A Neuromorphic Implementation of Multi-Factor Synaptic Plasticity With Calcium-Based Dynamics. IEEE Transactions on Circuits and Systems I - Regular papers, 63(12), 2189-2199. https://doi.org/10.1109/TCSI.2016.2616169
Engelmann, J., Walther, T., Grant, K., Chicca, E., & Gomez-Sena, L. (2016). Modeling latency code processing in the electric sense: from the biological template to its VLSI implementation. Bioinspiration & biomimetics, 11(5), Article 055007. https://doi.org/10.1088/1748-3190/11/5/055007

2015

Staar, B., Schirmer, M., Bai-Rossi, C., Micheli, G. D., Carrara, S., & Chicca, E. (2015). A neural approach to drugs monitoring for personalized medicine. In 2015 International Joint Conference on Neural Networks (IJCNN) IEEE. https://doi.org/10.1109/IJCNN.2015.7280611
Milde, M. B., Bertrand, O. J. N., Benosman, R., Egelhaaf, M., & Chicca, E. (2015). Bioinspired event-driven collision avoidance algorithm based on optic flow. In 2015 International Conference on Event-based Control, Communication, and Signal Processing (EBCCSP) IEEE. https://doi.org/10.1109/EBCCSP.2015.7300673
Richter, O., Reinhart, R. F., Nease, S., Steil, J., & Chicca, E. (2015). Device mismatch in a neuromorphic system implements random features for regression. 1-4. Paper presented at 2015 IEEE Biomedical Circuits and Systems Conference (BioCAS). https://doi.org/10.1109/BioCAS.2015.7348416
Nease, S., & Chicca, E. (2015). Power-Efficient Estimation of Silicon Neuron Firing Rates with Floating-Gate Transistors. In 2015 European Conference on Circuit Theory and Design (ECCTD) IEEE. https://doi.org/10.1109/ECCTD.2015.7300005
Thomas, A., Niehoerster, S., Fabretti, S., Shepheard, N., Kuschel, O., Kuepper, K., Wollschlaeger, J., Kzysteczko, P., & Chicca, E. (2015). Tunnel junction based memristors as artificial synapses. Frontiers in Neuroscience, 9, Article 241. https://doi.org/10.3389/fnins.2015.00241

2014

Perez-Peña, F., Linares-Barranco, A., & Chicca, E. (2014). An approach to motor control for spike-based neuromorphic robotics. In 2014 IEEE Biomedical Circuits and Systems Conference (BioCAS) Proceedings (pp. 528-531). IEEE. https://doi.org/10.1109/BioCAS.2014.6981779
Coath, M., Sheik, S., Chicca, E., Indiveri, G., Denham, S. L., & Wennekers, T. (2014). A robust sound perception model suitable for neuromorphic implementation. Frontiers in Neuroscience, 7, Article 278. https://doi.org/10.3389/fnins.2013.00278
Sandin, F., Khan, A. I., Dyer, A. G., Amin, A. H. M., Indiveri, G., Chicca, E., & Osipov, E. (2014). Concept Learning in Neuromorphic Vision Systems: What Can We Learn from Insects? Journal of Software Engineering and Applications, 7, 387-395. https://doi.org/10.4236/jsea.2014.75035
Ramachandran, H., Weber, S., Aamir, S. A., & Chicca, E. (2014). Neuromorphic Circuits for Short-term Plasticity with Recovery Control. In 2014 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 858-861). IEEE. https://doi.org/10.1109/ISCAS.2014.6865271
Chicca, E., Stefanini, F., Bartolozzi, C., & Indiveri, G. (2014). Neuromorphic Electronic Circuits for Building Autonomous Cognitive Systems. Proceedings of the IEEE, 102(9), 1367-1388. https://doi.org/10.1109/JPROC.2014.2313954
Chicca, E., Schmuker, M., & Nawrot, M. P. (2014). Neuromorphic Sensors, Olfaction. In D. Jaeger, & R. Jung (Eds.), Encyclopedia of Computational Neuroscience Springer New York LLC. https://doi.org/10.1007/978-1-4614-7320-6_119-2

2013

Rost, T., Ramachandran, H., Nawrot, M. P., & Chicca, E. (2013). A neuromorphic approach to auditory pattern recognition in cricket phonotaxis. In 2013 European Conference on Circuit Theory and Design (ECCTD) IEEE. https://doi.org/10.1109/ECCTD.2013.6662247
Aamir, S. A., Engelmann, J., Gomez, L., & Chicca, E. (2013). A Neuromorphic VLSI Implementation of a Simplified Electrosensory System in a Weakly Electric Fish.
Morabito, F. C., Andreou, A. G., & Chicca, E. (2013). Neuromorphic Engineering: From Neural Systems to Brain-Like Engineered Systems. Neural Networks, 45, 1-3. https://doi.org/10.1016/j.neunet.2013.07.001
Neftci, E., Binas, J., Rutishauser, U., Chicca, E., Indiveri, G., & Douglas, R. J. (2013). Synthesizing cognition in neuromorphic electronic systems. Proceedings of the National Academy of Sciences of the United States of America, 110(37), E3468-E3476. https://doi.org/10.1073/pnas.1212083110

2012

Sheik, S., Coath, M., Indiveri, G., Denham, S. L., Wennekers, T., & Chicca, E. (2012). Emergent auditory feature tuning in a real-time neuromorphic VLSI system. Frontiers in Neuroscience, 6, Article 17. https://doi.org/10.3389/fnins.2012.00017
Sheik, S., Chicca, E., & Indiveri, G. (2012). Exploiting Device Mismatch in Neuromorphic VLSI Systems to Implement Axonal Delays. In The 2012 International Joint Conference on Neural Networks (IJCNN) (pp. 1940-1945). IEEE. https://doi.org/10.1109/IJCNN.2012.6252636
Corneil, D., Sonnleithner, D., Neftci, E., Chicca, E., Cook, M., Indiveri, G., & Douglas, R. J. (2012). Function approximation with uncertainty propagation in a VLSI spiking neural network. In The 2012 International Joint Conference on Neural Networks (IJCNN) (pp. 2990-2996). IEEE. https://doi.org/10.1109/IJCNN.2012.6252780
Corneil, D., Sonnleithner, D., Neftci, E., Chicca, E., Cook, M., Indiveri, G., & Douglas, R. J. (2012). Real-time inference in a VLSI spiking neural network. In 2012 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 2425-2428). IEEE. https://doi.org/10.1109/ISCAS.2012.6271788
Neftci, E., Binas, J., Chicca, E., Indiveri, G., & Douglas, R. J. (2012). Systematic Construction of Finite State Automata Using VLSI Spiking Neurons. In T. J. Prescott, N. F. Lepora, A. Mura, & P. F. M. J. Verschure (Eds.), Biomimetic and Biohybrid Systems: First International Conference, Living Machines 2012, Barcelona, Spain, July 9-12, 2012. Proceedings (Vol. 7375, pp. 382-383). (Lecture Notes in Computer Science; Vol. 7375). Springer Berlin / Heidelberg. https://doi.org/10.1007/978-3-642-31525-1_52

2011

Neftci, E., Chicca, E., Indiveri, G., & Douglas, R. (2011). A Systematic Method for Configuring VLSI Networks of Spiking Neurons. Neural computation, 23(10), 2457-2497. https://doi.org/10.1162/NECO_a_00182
Indiveri, G., & Chicca, E. (2011). A VLSI neuromorphic device for implementing spike-based neural networks. In B. Apolloni, S. Bassis, A. Esposito, & C. F. Morabito (Eds.), Neural Nets WIRN11 - Proceedings of the 21st Italian Workshop on Neural Nets (Vol. 234, pp. 305-316). ( Frontiers in Artificial Intelligence and Applications; Vol. 234). IOS Press. https://doi.org/10.3233/978-1-60750-972-1-305
Sheik, S., Stefanini, F., Neftci, E., Chicca, E., & Indiveri, G. (2011). Systematic configuration and automatic tuning of neuromorphic systems. In 2011 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 873-876). IEEE. https://doi.org/10.1109/ISCAS.2011.5937705
Moraud, E. M., & Chicca, E. (2011). Toward Neuromorphic Odor Tracking: Perspectives for space exploration. Acta Futura, 4(8), 9-19. https://doi.org/10.2420/AF04.2011.09

2010

Beyeler, M., Stefanini, F., Proske, H., Galizia, G., & Chicca, E. (2010). Exploring Olfactory Sensory Networks: Simulations and Hardware Emulation. In 2010 Biomedical Circuits and Systems Conference (BioCAS) (pp. 270-273). IEEE. https://doi.org/10.1109/BIOCAS.2010.5709623
Neftci, E., Chicca, E., Cook, M., Indiveri, G., & Douglas, R. (2010). Live demonstration: State-dependent sensory processing in networks of VLSI spiking neurons. In ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems (pp. 2788). Article 5537006 IEEE. https://doi.org/10.1109/ISCAS.2010.5537006
Indiveri, G., Stefanini, F., & Chicca, E. (2010). Spike-based learning with a generalized integrate and fire silicon neuron. In Proceedings of 2010 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1951-1954). IEEE. https://doi.org/10.1109/ISCAS.2010.5536980
Emre, N., Chicca, E., Indiveri, G., & Douglas, R. (2010). State-dependent sensory processing in distributed networks of vlsi spiking neurons. Paper presented at 4th International Conference on Cognitive Systems, CogSys 2010, Zurich, Switzerland.
Neftci, E., Chicca, E., Cook, M., Indiveri, G., & Douglas, R. J. (2010). State-dependent sensory processing in networks of VLSI spiking neurons. In Proceedings of 2010 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 2789-2792). IEEE. https://doi.org/10.1109/ISCAS.2010.5537007

2009

Indiveri, G., Chicca, E., & Douglas, R. J. (2009). Artificial Cognitive Systems: From VLSI Networks of Spiking Neurons to Neuromorphic Cognition. Cognitive computation, 1(2), 119-127. https://doi.org/10.1007/s12559-008-9003-6

2008

Neftci, E., Chicca, E., Indiveri, G., Slotine, J.-J., & Douglas, R. J. (2008). Contraction Properties of VLSI Cooperative Competitive Neural Networks of Spiking Neurons. In J. C. Platt, D. Koller, Y. Singer, & S. Roweis (Eds.), Advances in Neural Information Processing Systems (NIPS) (Vol. 20, pp. 1073-1080). The MIT Press.
Tapson, J., Diaz, J., Sander, D., Gurari, N., Chicca, E., Pouliquen, P., & Etienne-Cummings, R. (2008). The Feeling of Color: A Haptic Feedback Device for the Visually Disabled. In 2008 IEEE Biomedical Circuits and Systems Conference (BIOCAS) (pp. 381-384). IEEE. https://doi.org/10.1109/BIOCAS.2008.4696954

2007

Chicca, E., Whatley, A. M., Lichtsteiner, P., Dante, V., Delbruck, T., Del Giudice, P., Douglas, R. J., & Indiveri, G. (2007). A Multichip Pulse-Based Neuromorphic Infrastructure and Its Application to a Model of Orientation Selectivity. IEEE Transactions on Circuits and Systems I - Regular papers, 54(5), 981-993. https://doi.org/10.1109/TCSI.2007.893509
Chicca, E., Indiveri, G., & Douglas, R. J. (2007). Context dependent amplification of both rate and event-correlation in a VLSI network of spiking neurons. In B. Schölkopf, J. Platt, & T. Hofmann (Eds.), Advances in Neural Information Processing Systems 19 - Proceedings of the 2006 Conference (pp. 257-264). (Advances in Neural Information Processing Systems). MIT Press.
Wang, H.-P., Chicca, E., Indiveri, G., & Sejnowski, T. J. (2007). Reliable Computation in Noisy Backgrounds Using Real-Time Neuromorphic Hardware. In 2007 IEEE Biomedical Circuits and Systems Conference (BioCAS) (pp. 71-74). IEEE. https://doi.org/10.1109/BIOCAS.2007.4463311

2006

Chicca, E. (2006). A Neuromorphic VLSI System for Modeling Spike-Based Cooperative Competitive Neural Networks. [Thesis fully external, UNI, ETH Zurich, ETH, Inst Neuroinformat]. ETH Zurich. https://doi.org/10.3929/ethz-a-005275753
Indiveri, G., Chicca, E., & Douglas, R. (2006). A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity. IEEE Transactions on Neural Networks, 17(1), 211-221. https://doi.org/10.1109/TNN.2005.860850
Chicca, E., Lichtsteiner, P., Delbruck, T., Indiveri, G., & Douglas, R. J. (2006). Modeling Orientation Selectivity Using a Neuromorphic Multi-Chip System. In 2006 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1235-1238). IEEE. https://doi.org/10.1109/ISCAS.2006.1692815

2004

Chicca, E., Indiveri, G., & Douglas, R. J. (2004). An event-based VLSI network of integrate-and-fire neurons. In 2004 IEEE International Symposium on Circuits and Systems (ISCAS) (Vol. 5). IEEE. https://doi.org/10.1109/ISCAS.2004.1329536
Indiveri, G., Chicca, E., & Douglas, R. J. (2004). A VLSI reconfigurable network of integrate-and-fire neurons with spike-based learning synapses. In Proceedings of 12th European Symposium on Artificial Neural Networks (ESANN04) (pp. 405-410). ESANN.
Rubin, D. B., Chicca, E., & Indiveri, G. (2004). Characterizing the firing properties of an adaptive analog VLSI neuron. In AJ. Ijspeert, M. Murata, & N. Wakamiya (Eds.), Biologically Inspired Approaches to Advanced Information Technology (pp. 189-200). (Lecture Notes in Computer Science; Vol. 3141). Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-540-27835-1_15
Rubin, D. B.-D., Chicca, E., & Indiveri, G. (2004). Firing proprieties of an adaptive analog VLSI neuron. In Proceedings of Bio-ADIT 2004 , Lausanne (pp. 314-327)

2003

Chicca, E., Indiveri, G., & Douglas, R. J. (2003). An adaptive silicon synapse. In Proceedings of the 2003 International Symposium on Circuits and Systems ISCAS '03 (pp. I81-I84). IEEE. https://doi.org/10.1109/ISCAS.2003.1205505
Chicca, E., Badoni, D., Dante, V., D'Andreagiovanni, M., Salina, G., Carota, L., Fusi, S., & Del Giudice, P. (2003). A VLSI recurrent network of integrate-and-fire neurons connected by plastic synapses with long-term memory. IEEE Transactions on Neural Networks, 14(5), 1297-1307. https://doi.org/10.1109/TNN.2003.816367

2001

Chicca, E., & Fusi, S. (2001). Stochastic synaptic plasticity in deterministic aVLSI networks of spiking neurons. In F. Rattay (Ed.), Proceedings of the World Congress on Neuroinformatics (pp. 468-477). (ARGESIM Reports). ARGESIM/ASIM Verlag.
Last modified:09 June 2023 8.36 p.m.