Cache performance of video computation workloads. - Stefan Petko; Dhireesha Kudithipudi; Eugene John (DCV, 2002)

Impact of nanotechnology on the performance of CMOS digital multipliers. - Dhireesha Kudithipudi; R. Kotha; Eugene John; Z. Pantic-Tanner (Circuits, Signals, and Systems, 2004)

Parametrical characterization of leakage power in embedded system caches using gated-VSS. - Dhireesha Kudithipudi; Eugene John (Circuits, Signals, and Systems, 2005)

Implementation of Low Power Digital Multipliers using 10 -Transistor Adder Blocks. - Dhireesha Kudithipudi; Eugene John (J. Low Power Electron., 2005)

Performance Analysis of Embedded Applications on a Pentium-4 Based Machine. - Pradeep S. Nair; Dhireesha Kudithipudi; Eugene John; Fred W. Hudson (ESA, 2006)

Static Power Analysis and Estimation in Ternary Content Addressable Memory Cells. - Dhireesha Kudithipudi; Eugene John (J. Low Power Electron., 2007)

GALEOR: Leakage reduction for CMOS circuits. - Srikanth Katrue; Dhireesha Kudithipudi (ICECS, 2008)

Caches for Multimedia Workloads: Power and Energy Tradeoffs. - Dhireesha Kudithipudi; Stefan Petko; Eugene B. John (IEEE Trans. Multim., 2008)

Topology selection of FPGA look-up tables for low-leakage operation. - Pradeep S. Nair; Santosh Koppa; Eugene B. John; Dhireesha Kudithipudi (ECCTD, 2009)

Implications of gated-Vss technique on leakage power in embedded caches. - Dhireesha Kudithipudi; Eugene John (Int. J. Embed. Syst., 2009)

Performance enhancement of subthreshold circuits using substrate biasing and charge-boosting buffers. - Sumanth Amarchinta; Dhireesha Kudithipudi (ACM Great Lakes Symposium on VLSI, 2010)

Variation tolerant 9T SRAM cell design. - Sreeharsha Tavva; Dhireesha Kudithipudi (ACM Great Lakes Symposium on VLSI, 2010)

Ultra low energy standard cell design optimization for performance and placement algorithm. - Sumanth Amarchinta; Dhireesha Kudithipudi (Green Computing Conference, 2010)

Towards integrated circuit thermal profiling for reduced power consumption: Evaluation of distributed sensing techniques. - Andres Kwasinski; Dhireesha Kudithipudi (Green Computing Conference, 2010)

Characterization of Variation Aware Nanoscale Static Random Access Memory Designs. - Sreeharsha Tavva; Dhireesha Kudithipudi (J. Low Power Electron., 2010)

Cooling mechanisms in 3D ICs: Thermo-mechanical perspective. - Satish G. Kandlikar; Dhireesha Kudithipudi; Carlos A. Rubio-Jimenez (IGCC, 2011)

Reconfigurable N-level memristor memory design. - Cory E. Merkel; Nakul Nagpal; Sindhura Mandalapu; Dhireesha Kudithipudi (IJCNN, 2011)

Execution characteristics of embedded applications on a Pentium 4-based personal computer. - Pradeep S. Nair; Dhireesha Kudithipudi; Eugene B. John; Fred W. Hudson (J. Embed. Comput., 2011)

Hybrid Subthreshold and Nearthreshold Design Methodology for Energy Minimization. - J. Kevin Hicks; Dhireesha Kudithipudi (J. Low Power Electron., 2011)

Design-time performance evaluation of thermal management policies for SRAM and RRAM based 3D MPSoCs. - David Brenner; Cory E. Merkel; Dhireesha Kudithipudi (ACM Great Lakes Symposium on VLSI, 2012)

Temperature-aware computing: Achievements and remaining challenges. - Dhireesha Kudithipudi; Ayse K. Coskun; Sherief Reda; Qinru Qiu (IGCC, 2012)

RRAM Motifs for Mitigating Differential Power Analysis Attacks (DPA). - Ganesh Khedkar; Dhireesha Kudithipudi (ISVLSI, 2012)

RRAM-based adaptive neural logic block for implementing non-linearly separable functions in a single layer. - Michael Soltiz; Cory E. Merkel; Dhireesha Kudithipudi; Garrett S. Rose (NANOARCH, 2012)

Reconfigurable RRAM for LUT logic mapping: A case study for reliability enhancement. - Matthew Catanzaro; Dhireesha Kudithipudi (SoCC, 2012)

Lightweight energy prediction framework for solar-powered wireless sensor networks. - Cory E. Merkel; Dhireesha Kudithipudi; Andres Kwasinski (SoCC, 2012)

Towards Thermal Profiling in CMOS/Memristor Hybrid RRAM Architectures. - Cory E. Merkel; Dhireesha Kudithipudi (VLSI Design, 2012)

Subthreshold Computing. - J. Kevin Hicks; Dhireesha Kudithipudi (Handbook of Energy-Aware and Green Computing, 2012)

Periodic activation functions in memristor-based analog neural networks. - Cory E. Merkel; Dhireesha Kudithipudi; Nick Sereni (IJCNN, 2013)

Memristor-Based Neural Logic Blocks for Nonlinearly Separable Functions. - Michael Soltiz; Dhireesha Kudithipudi; Cory E. Merkel; Garrett S. Rose; Robinson E. Pino (IEEE Trans. Computers, 2013)

Thermal Management in Many Core Systems. - Dhireesha Kudithipudi; Qinru Qiu; Ayse K. Coskun (Evolutionary Based Solutions for Green Computing, 2013)

Memristive Reservoir Computing Architecture for Epileptic Seizure Detection. - Cory E. Merkel; Qutaiba Saleh; Colin Donahue; Dhireesha Kudithipudi (BICA, 2014)

A current-mode CMOS/memristor hybrid implementation of an extreme learning machine. - Cory E. Merkel; Dhireesha Kudithipudi (ACM Great Lakes Symposium on VLSI, 2014)

Neuromemristive Extreme Learning Machines for Pattern Classification. - Cory E. Merkel; Dhireesha Kudithipudi (ISVLSI, 2014)

On designing circuit primitives for cortical processors with memristive hardware. - Dhireesha Kudithipudi; Cory E. Merkel; Yu Kee Ooi; Qutaiba Saleh; Garrett S. Rose (SoCC, 2014)

A stochastic learning algorithm for neuromemristive systems. - Cory E. Merkel; Dhireesha Kudithipudi (SoCC, 2014)

Temperature Sensing RRAM Architecture for 3-D ICs. - Cory E. Merkel; Dhireesha Kudithipudi (IEEE Trans. Very Large Scale Integr. Syst., 2014)

Design of Neuromorphic Architectures with Memristors. - Dhireesha Kudithipudi; Cory E. Merkel; Michael Soltiz; Garrett S. Rose; Robinson E. Pino (Network Science and Cybersecurity, 2014)

Nanoelectronics and Hardware Security. - Garrett S. Rose; Dhireesha Kudithipudi; Ganesh Khedkar; Nathan R. McDonald; Bryant T. Wysocki; Lok-Kwong Yan (Network Science and Cybersecurity, 2014)

Design and analysis of neuromemristive echo state networks with limited-precision synapses. - Colin Donahue; Cory E. Merkel; Qutaiba Saleh; Levs Dolgovs; Yu Kee Ooi; Dhireesha Kudithipudi; Bryant T. Wysocki (CISDA, 2015)

Memristive computational architecture of an echo state network for real-time speech-emotion recognition. - Qutaiba Saleh; Cory E. Merkel; Dhireesha Kudithipudi; Bryant T. Wysocki (CISDA, 2015)

Reconfigurable hardware architecture of the spatial pooler for hierarchical temporal memory. - Abdullah M. Zyarah; Dhireesha Kudithipudi (SoCC, 2015)

Comparison of Off-Chip Training Methods for Neuromemristive Systems. - Cory E. Merkel; Dhireesha Kudithipudi (VLSID, 2015)

Digital neuromorphic design of a Liquid State Machine for real-time processing. - Anvesh Polepalli; Nicholas Soures; Dhireesha Kudithipudi (ICRC, 2016)

A design of HTM spatial pooler for face recognition using memristor-CMOS hybrid circuits. - Timur Ibrayev; Alex Pappachen James; Cory E. Merkel; Dhireesha Kudithipudi (ISCAS, 2016)

Invited: Towards a scalable neuromorphic hardware for classification and prediction with stochastic No-Prop algorithms. - Dan Christiani; Cory E. Merkel; Dhireesha Kudithipudi (ISQED, 2016)

Reconfigurable Digital Design of a Liquid State Machine for Spatio-Temporal Data. - Anvesh Polepalli; Dhireesha Kudithipudi (NANOCOM, 2016)

Neuromemristive Systems: Boosting Efficiency through Brain-Inspired Computing. - Cory E. Merkel; Raqibul Hasan; Nicholas Soures; Dhireesha Kudithipudi; Tarek M. Taha; Sapan Agarwal; Matthew J. Marinella (Computer, 2016)

Unsupervised Learning in Neuromemristive Systems. - Cory E. Merkel; Dhireesha Kudithipudi (CoRR, 2016)

A Mathematical Formalization of Hierarchical Temporal Memory Cortical Learning Algorithm's Spatial Pooler. - James Mnatzaganian; Ernest Fokoué; Dhireesha Kudithipudi (CoRR, 2016)

Non-volatile Hierarchical Temporal Memory: Hardware for Spatial Pooling. - Lennard Streat; Dhireesha Kudithipudi; Kevin Gomez (CoRR, 2016)

A Mathematical Formalization of Hierarchical Temporal Memory's Spatial Pooler. - James Mnatzaganian; Ernest Fokoué; Dhireesha Kudithipudi (Frontiers Robotics AI, 2016)

Convolutional Drift Networks for Video Classification. - Dillon Graham; Seyed Hamed Fatemi Langroudi; Christopher Kanan; Dhireesha Kudithipudi (ICRC, 2017)

A penalized maximum likelihood approach to the adaptive learning of the spatial pooler permanence. - Ernest Fokoué; Lakshmi Ravi; Dhireesha Kudithipudi (IJCNN, 2017)

Robustness of a memristor based liquid state machine. - Nicholas Soures; Lydia Hays; Dhireesha Kudithipudi (IJCNN, 2017)

Extreme learning machine as a generalizable classification engine. - Abdullah M. Zyarah; Dhireesha Kudithipudi (IJCNN, 2017)

Ziksa: On-chip learning accelerator with memristor crossbars for multilevel neural networks. - Abdullah M. Zyarah; Nicholas Soures; Lydia Hays; Robin Jacobs-Gedrim; Sapan Agarwal; Matthew J. Marinella; Dhireesha Kudithipudi (ISCAS, 2017)

On-device STDP and synaptic normalization for neuromemristive spiking neural network. - Nicholas Soures; Lydia Hays; Eric Bohannon; Abdullah M. Zyarah; Dhireesha Kudithipudi (MWSCAS, 2017)

Invited paper: Resource sharing in feed forward neural networks for energy efficiency. - Abdullah M. Zyarah; Dhireesha Kudithipudi (MWSCAS, 2017)

On accelerating stochastic neural networks. - Swathika Ramakrishnan; Dhireesha Kudithipudi (NANOCOM, 2017)

Reservoir Computing in Embedded Systems: Three variants of the reservoir algorithm. - Nicholas Soures; Corey Merkel; Dhireesha Kudithipudi; Clare Thiem; Nathan R. McDonald (IEEE Consumer Electron. Mag., 2017)

Stochastic CBRAM-Based Neuromorphic Time Series Prediction System. - Cory E. Merkel; Dhireesha Kudithipudi; Manan Suri; Bryant T. Wysocki (ACM J. Emerg. Technol. Comput. Syst., 2017)

HTM Spatial Pooler With Memristor Crossbar Circuits for Sparse Biometric Recognition. - Alex Pappachen James; Irina Fedorova; Timur Ibrayev; Dhireesha Kudithipudi (IEEE Trans. Biomed. Circuits Syst., 2017)

Editorial: A Successful Year and Looking Forward to 2017 and Beyond. - Haibo He; Robert Haas; Jun Fu; Barbara Hammer; Daniel W. C. Ho; Fakhri Karray; Dhireesha Kudithipudi; José Antonio Lozano 001; Teresa Bernarda Ludermir; Jacek Mandziuk; Stefano Melacci; Antonio Paiva; et al. (IEEE Trans. Neural Networks Learn. Syst., 2017)

Scalable IP Core for Feed Forward Random Networks. - Anurag Reddy Daram; Karan Paluru; Vedant Karia; Dhireesha Kudithipudi (ELM, 2018)

Deep Learning Inference on Embedded Devices: Fixed-Point vs Posit. - Seyed Hamed Fatemi Langroudi; Tej Pandit; Dhireesha Kudithipudi (EMC2@ASPLOS, 2018)

On-Device Learning in Memristor Spiking Neural Networks. - Abdullah M. Zyarah; Nicholas Soures; Dhireesha Kudithipudi (ISCAS, 2018)

Secure Neural Circuits to Mitigate Correlation Power Analysis on SHA-3 Hash Function. - James Thesing; Dhireesha Kudithipudi (VLSID, 2018)

On the Statistical Challenges of Echo State Networks and Some Potential Remedies. - Qiuyi Wu; Ernest Fokoué; Dhireesha Kudithipudi (CoRR, 2018)

Mod-DeepESN: Modular Deep Echo State Network. - Zachariah Carmichael; Humza Syed; Stuart Burtner; Dhireesha Kudithipudi (CoRR, 2018)

Semi-Trained Memristive Crossbar Computing Engine with In-Situ Learning Accelerator. - Abdullah M. Zyarah; Dhireesha Kudithipudi (CoRR, 2018)

Semi-Trained Memristive Crossbar Computing Engine with In Situ Learning Accelerator. - Abdullah M. Zyarah; Dhireesha Kudithipudi (ACM J. Emerg. Technol. Comput. Syst., 2018)

Neuromorphic and cognitive computing and communication in hardware. - Yang Cindy Yi; Dhireesha Kudithipudi (Nano Commun. Networks, 2018)

Deep Positron: A Deep Neural Network Using the Posit Number System. - Zachariah Carmichael; Hamed Fatemi Langroudi; Char Khazanov; Jeffrey Lillie; John L. Gustafson; Dhireesha Kudithipudi (DATE, 2019)

Stochastic Tucker-Decomposed Recurrent Neural Networks for Forecasting. - Zachariah Carmichael; Dhireesha Kudithipudi (GlobalSIP, 2019)

Exploiting Randomness in Deep Learning Algorithms. - Hamed Fatemi Langroudi; Cory E. Merkel; Humza Syed; Dhireesha Kudithipudi (IJCNN, 2019)

Neuromemristive Multi-Layer Random Projection Network with On-Device Learning. - Abdullah M. Zyarah; Dhireesha Kudithipudi (IJCNN, 2019)

Task-Based Neuromodulation Architecture for Lifelong Learning. - Anurag Reddy Daram; Dhireesha Kudithipudi; Angel Yanguas-Gil (ISQED, 2019)

Performance-Efficiency Trade-off of Low-Precision Numerical Formats in Deep Neural Networks. - Zachariah Carmichael; Hamed Fatemi Langroudi; Char Khazanov; Jeffrey Lillie; John L. Gustafson; Dhireesha Kudithipudi (CoRR, 2019)

Deep Learning Training on the Edge with Low-Precision Posits. - Hamed Fatemi Langroudi; Zachariah Carmichael; Dhireesha Kudithipudi (CoRR, 2019)

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge. - Hamed Fatemi Langroudi; Zachariah Carmichael; David Pastuch; Dhireesha Kudithipudi (CoRR, 2019)

Analysis of Wide and Deep Echo State Networks for Multiscale Spatiotemporal Time Series Forecasting. - Zachariah Carmichael; Humza Syed; Dhireesha Kudithipudi (CoRR, 2019)

Neuromemrisitive Architecture of HTM with On-Device Learning and Neurogenesis. - Abdullah M. Zyarah; Dhireesha Kudithipudi (ACM J. Emerg. Technol. Comput. Syst., 2019)

Spiking Reservoir Networks: Brain-inspired recurrent algorithms that use random, fixed synaptic strengths. - Nicholas Soures; Dhireesha Kudithipudi (IEEE Signal Process. Mag., 2019)

Guest Editorial: Special Issue on New Trends in Smart Chips and Smart Hardware. - Guang-Bin Huang; E. S. Eleftheriou; Dhireesha Kudithipudi; Jonathan Tapson; Hao Yu 001 (IEEE Trans. Emerg. Top. Comput. Intell., 2019)

Neuromorphic Architecture for the Hierarchical Temporal Memory. - Abdullah M. Zyarah; Dhireesha Kudithipudi (IEEE Trans. Emerg. Top. Comput. Intell., 2019)

Adaptive Posit: Parameter aware numerical format for deep learning inference on the edge. - Hamed Fatemi Langroudi; Vedant Karia; John L. Gustafson; Dhireesha Kudithipudi (CVPR Workshops, 2020)

Metaplasticity in Multistate Memristor Synaptic Networks. - Fatima Tuz Zohora; Abdullah M. Zyarah; Nicholas Soures; Dhireesha Kudithipudi (ISCAS, 2020)

FeFET-Based Neuromorphic Architecture with On-Device Feedback Alignment Training. - Sumin Jot; Abdullah M. Zyarah; Santosh Kurinec; Kai Ni 004; Fatima Tuz Zohora; Dhireesha Kudithipudi (ISQED, 2020)

Relational Neurogenesis for Lifelong Learning Agents. - Tej Pandit; Dhireesha Kudithipudi (NICE, 2020)

End-to-End Memristive HTM System for Pattern Recognition and Sequence Prediction. - Abdullah M. Zyarah; Kevin Gomez; Dhireesha Kudithipudi (CoRR, 2020)

Neuromorphic System for Spatial and Temporal Information Processing. - Abdullah M. Zyarah; Kevin Gomez; Dhireesha Kudithipudi (IEEE Trans. Computers, 2020)

ALPS: Adaptive Quantization of Deep Neural Networks With GeneraLized PositS. - Hamed Fatemi Langroudi; Vedant Karia; Zachariah Carmichael; Abdullah M. Zyarah; Tej Pandit; John L. Gustafson; Dhireesha Kudithipudi (CVPR Workshops, 2021)

MetaplasticNet: Architecture with Probabilistic Metaplastic Synapses for Continual Learning. - Fatima Tuz Zohora; Vedant Karia; Anurag Reddy Daram; Abdullah M. Zyarah; Dhireesha Kudithipudi (ISCAS, 2021)

TENT: Efficient Quantization of Neural Networks on the tiny Edge with Tapered FixEd PoiNT. - Hamed Fatemi Langroudi; Vedant Karia; Tej Pandit; Dhireesha Kudithipudi (CoRR, 2021)

Toward Near-Real-Time Training With Semi-Random Deep Neural Networks and Tensor-Train Decomposition. - Humza Syed; Ryan Bryla; Uttam K. Majumder; Dhireesha Kudithipudi (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021)

ACTION: Automated Hardware-Software Codesign Framework for Low-precision Numerical Format SelecTION in TinyML. - Hamed Fatemi Langroudi; Vedant Karia; Tej Pandit; Becky Mashaido; Dhireesha Kudithipudi (CoNGA, 2022)

Low-Shot Learning and Pattern Separation using Cellular Automata Integrated CNNs. - Tej Pandit; Dhireesha Kudithipudi (ICONS, 2022)

SCOLAR: A Spiking Digital Accelerator with Dual Fixed Point for Continual Learning. - Vedant Karia; Fatima Tuz Zohora; Nicholas Soures; Dhireesha Kudithipudi (ISCAS, 2022)

Biological underpinnings for lifelong learning machines. - Dhireesha Kudithipudi; Mario Aguilar-Simon; Jonathan Babb; Maxim Bazhenov; Douglas Blackiston; Josh C. Bongard; Andrew P. Brna; Suraj Chakravarthi Raja; Nick Cheney; Jeff Clune; Anurag Reddy Daram; Stefano Fusi; et al. (Nat. Mach. Intell., 2022)

Context Modulation Enables Multi-tasking and Resource Efficiency in Liquid State Machines. - Peter Helfer; Corinne Teeter; Aaron J. Hill; Craig M. Vineyard; James B. Aimone; Dhireesha Kudithipudi (ICONS, 2023)

NEO: Neuron State Dependent Mechanisms for Efficient Continual Learning. - Anurag Reddy Daram; Dhireesha Kudithipudi (NICE, 2023)

NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking. - Jason Yik; Soikat Hasan Ahmed; Zergham Ahmed; Brian Anderson; Andreas G. Andreou; Chiara Bartolozzi; Arindam Basu; Douwe den Blanken; Petrut Bogdan; Sander M. Bohté; Younes Bouhadjar; Sonia M. Buckley; et al. (CoRR, 2023)

Design Principles for Lifelong Learning AI Accelerators. - Dhireesha Kudithipudi; Anurag Reddy Daram; Abdullah M. Zyarah; Fatima Tuz Zohora; James B. Aimone; Angel Yanguas-Gil; Nicholas Soures; Emre Neftci; Matthew Mattina; Vincenzo Lomonaco; Clare D. Thiem; Benjamin R. Epstein (CoRR, 2023)

A domain-agnostic approach for characterization of lifelong learning systems. - Megan M. Baker; Alexander New; Mario Aguilar-Simon; Ziad Al-Halah; Sébastien M. R. Arnold; Eseoghene Ben-Iwhiwhu; Andrew P. Brna; Ethan Brooks; Ryan C. Brown; Zachary Daniels; Anurag Reddy Daram; Fabien Delattre; et al. (Neural Networks, 2023)

Advancing Neuro-Inspired Lifelong Learning for Edge with Co-Design. - Nicholas Soures; Vedant Karia; Dhireesha Kudithipudi (AAAI Spring Symposia, 2024)

PositCL: Compact Continual Learning with Posit Aware Quantization. - Vedant Karia; Abdullah M. Zyarah; Dhireesha Kudithipudi (ACM Great Lakes Symposium on VLSI, 2024)

Energy Efficiency Scaling for 2 Decades (EES2) Roadmap for Computing. - T. Kaarsberg; J. Atulasimha; J. Baniecki; P. Fischer; S. Pawlowski; S. Misra; A. Bhavnagarwala; E. Salman; M. Ahmed; N. Li; R. Aggarwal; B. Hirano; et al. (HPEC, 2024)

Continual Learning and Catastrophic Forgetting. - Gido M. van de Ven; Nicholas Soures; Dhireesha Kudithipudi (CoRR, 2024)

Probabilistic Metaplasticity for Continual Learning with Memristors. - Fatima Tuz Zohora; Vedant Karia; Nicholas Soures; Dhireesha Kudithipudi (CoRR, 2024)

Watch Your Step: Optimal Retrieval for Continual Learning at Scale. - Truman Hickok; Dhireesha Kudithipudi (CoRR, 2024)

TACOS: Task Agnostic Continual Learning in Spiking Neural Networks. - Nicholas Soures; Peter Helfer; Anurag Reddy Daram; Tej Pandit; Dhireesha Kudithipudi (CoRR, 2024)

Continual Learning: Applications and the Road Forward. - Eli Verwimp; Rahaf Aljundi; Shai Ben-David; Matthias Bethge; Andrea Cossu; Alexander Gepperth; Tyler L. Hayes; Eyke Hüllermeier; Christopher Kanan; Dhireesha Kudithipudi; Christoph H. Lampert; Martin Mundt; et al. (Trans. Mach. Learn. Res., 2024)

Learning Continually in Silicon. - Nicholas Soures; Jayanta Dey; Dhireesha Kudithipudi (Computer, 2024)

Reservoir Network With Structural Plasticity for Human Activity Recognition. - Abdullah M. Zyarah; Alaa M. Abdul-Hadi; Dhireesha Kudithipudi (IEEE Trans. Emerg. Top. Comput. Intell., 2024)

Does Alignment help continual learning? - Anurag Reddy Daram; Dhireesha Kudithipudi (CLD2, 2025)

Time-Series Forecasting and Sequence Learning Using Memristor-based Reservoir System. - Abdullah M. Zyarah; Dhireesha Kudithipudi (ACM Trans. Embed. Comput. Syst., 2025)

Minion Gated Recurrent Unit for Continual Learning. - Abdullah M. Zyarah; Dhireesha Kudithipudi (CoRR, 2025)

Temporal Chunking Enhances Recognition of Implicit Sequential Patterns. - Jayanta Dey; Nicholas Soures; Miranda Gonzales; Itamar Lerner; Christopher Kanan; Dhireesha Kudithipudi (CoRR, 2025)

Voltage Mode Winner-Take-All Circuit for Neuromorphic Systems. - Abdullah M. Zyarah; Dhireesha Kudithipudi (CoRR, 2025)