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2020 – today
- 2022
[j57]Geoffrey W. Burr
, SukHwan Lim, Boris Murmann, Rangharajan Venkatesan, Marian Verhelst:
Fair and Comprehensive Benchmarking of Machine Learning Processing Chips. IEEE Des. Test 39(3): 18-27 (2022)- [j56]Vikram Jain, Ninad Jadhav, Marian Verhelst:
Enabling real-time object detection on low cost FPGAs. J. Real Time Image Process. 19(1): 217-229 (2022) - [j55]Nimish Shah, Laura Isabel Galindez Olascoaga, Shirui Zhao, Wannes Meert, Marian Verhelst:
DPU: DAG Processing Unit for Irregular Graphs With Precision-Scalable Posit Arithmetic in 28 nm. IEEE J. Solid State Circuits 57(8): 2586-2596 (2022) - [j54]Ehab M. Ibrahim, Linyan Mei, Marian Verhelst:
Taxonomy and Benchmarking of Precision-Scalable MAC Arrays Under Enhanced DNN Dataflow Representation. IEEE Trans. Circuits Syst. I Regul. Pap. 69(5): 2013-2024 (2022) - [j53]Nimish Shah, Wannes Meert, Marian Verhelst:
GraphOpt: Constrained-Optimization-Based Parallelization of Irregular Graphs. IEEE Trans. Parallel Distributed Syst. 33(12): 3321-3332 (2022) - [c110]Steven Colleman, Peter Zhu, Wei Sun, Marian Verhelst:
Optimizing Accelerator Configurability for Mobile Transformer Networks. AICAS 2022: 142-145 - [c109]Linyan Mei, Huichu Liu, Tony F. Wu, H. Ekin Sumbul, Marian Verhelst, Edith Beigné:
A Uniform Latency Model for DNN Accelerators with Diverse Architectures and Dataflows. DATE 2022: 220-225 - [c108]Shirui Zhao, Nimish Shah, Wannes Meert, Marian Verhelst:
Discrete Samplers for Approximate Inference in Probabilistic Machine Learning. DATE 2022: 1221-1226 - [c107]Kodai Ueyoshi, Ioannis A. Papistas, Pouya Houshmand, Giuseppe M. Sarda, Vikram Jain, Man Shi, Qilin Zheng, Juan Sebastian P. Giraldo, Peter Vrancx, Jonas Doevenspeck, Debjyoti Bhattacharjee, Stefan Cosemans, Arindam Mallik, Peter Debacker, Diederik Verkest, Marian Verhelst:
DIANA: An End-to-End Energy-Efficient Digital and ANAlog Hybrid Neural Network SoC. ISSCC 2022: 1-3 - [c106]Vikram Jain, Juan Sebastian P. Giraldo, Jaro De Roose, Bert Boons, Linyan Mei, Marian Verhelst:
TinyVers: A 0.8-17 TOPS/W, 1.7 μW-20 mW, Tiny Versatile System-on-chip with State-Retentive eMRAM for Machine Learning Inference at the Extreme Edge. VLSI Technology and Circuits 2022: 20-21 - [i17]Zuzana Jelcicová, Marian Verhelst:
Delta Keyword Transformer: Bringing Transformers to the Edge through Dynamically Pruned Multi-Head Self-Attention. CoRR abs/2204.03479 (2022) - [i16]Maxim Bonnaerens, Matthias Freiberger, Marian Verhelst, Joni Dambre:
Hardware-aware mobile building block evaluation for computer vision. CoRR abs/2208.12694 (2022) - 2021
- [j52]Tom Vermeulen, Brecht Reynders, Fernando E. Rosas, Marian Verhelst, Sofie Pollin:
Performance analysis of in-band collision detection for dense wireless networks. EURASIP J. Wirel. Commun. Netw. 2021(1): 87 (2021) - [j51]Man Shi, Pouya Houshmand, Linyan Mei, Marian Verhelst:
Hardware-Efficient Residual Neural Network Execution in Line-Buffer Depth-First Processing. IEEE J. Emerg. Sel. Topics Circuits Syst. 11(4): 690-700 (2021) - [j50]Linyan Mei, Pouya Houshmand, Vikram Jain, Juan Sebastian P. Giraldo, Marian Verhelst:
ZigZag: Enlarging Joint Architecture-Mapping Design Space Exploration for DNN Accelerators. IEEE Trans. Computers 70(8): 1160-1174 (2021) - [j49]Tom R. Molderez, Korneel Rabaey, Marian Verhelst:
A Scalable 128-Channel, Time-Multiplexed Potentiostat for Parallel Electrochemical Experiments. IEEE Trans. Circuits Syst. I Regul. Pap. 68(3): 1068-1079 (2021) - [j48]Juan Sebastian P. Giraldo, Marian Verhelst:
Hardware Acceleration for Embedded Keyword Spotting: Tutorial and Survey. ACM Trans. Embed. Comput. Syst. 20(6): 111:1-111:25 (2021) - [j47]Steven Colleman, Marian Verhelst:
High-Utilization, High-Flexibility Depth-First CNN Coprocessor for Image Pixel Processing on FPGA. IEEE Trans. Very Large Scale Integr. Syst. 29(3): 461-471 (2021) - [j46]Juan Sebastian P. Giraldo, Vikram Jain, Marian Verhelst:
Efficient Execution of Temporal Convolutional Networks for Embedded Keyword Spotting. IEEE Trans. Very Large Scale Integr. Syst. 29(12): 2220-2228 (2021) - [c105]Vikram Jain, Linyan Mei, Marian Verhelst:
Analyzing the Energy-Latency-Area-Accuracy Trade-off Across Contemporary Neural Networks. AICAS 2021: 1-4 - [c104]Arne Symons, Linyan Mei, Marian Verhelst:
LOMA: Fast Auto-Scheduling on DNN Accelerators through Loop-Order-based Memory Allocation. AICAS 2021: 1-4 - [c103]Peishuo Li, Tom R. Molderez, Marian Verhelst:
A 96-channel 40nm CMOS Fully-Integrated Potentiostat for Electrochemical Monitoring. ESSCIRC 2021: 167-170 - [c102]Peishuo Li, Tom R. Molderez, Marian Verhelst:
A 96-channel 40nm CMOS Fully-Integrated Potentiostat for Electrochemical Monitoring. ESSDERC 2021: 167-170 - [c101]Zuzana Jelcicová, Rasmus Jones, David Thorn Blix, Marian Verhelst, Jens Sparsø:
PeakRNN and StatsRNN: Dynamic Pruning in Recurrent Neural Networks. EUSIPCO 2021: 416-420 - [c100]Nimish Shah, Laura Isabel Galindez Olascoaga, Shirui Zhao, Wannes Meert, Marian Verhelst:
9.4 PIU: A 248GOPS/W Stream-Based Processor for Irregular Probabilistic Inference Networks Using Precision-Scalable Posit Arithmetic in 28nm. ISSCC 2021: 150-152 - [c99]Steven Colleman, Thomas Verelst, Linyan Mei, Tinne Tuytelaars, Marian Verhelst:
Processor Architecture Optimization for Spatially Dynamic Neural Networks. VLSI-SoC 2021: 1-6 - [c98]Koen Goetschalckx, Marian Verhelst:
DepFiN: A 12nm, 3.8TOPs depth-first CNN processor for high res. image processing. VLSI Circuits 2021: 1-2 - [i15]Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst:
ProbLP: A framework for low-precision probabilistic inference. CoRR abs/2103.00216 (2021) - [i14]Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst:
Acceleration of probabilistic reasoning through custom processor architecture. CoRR abs/2103.00266 (2021) - [i13]Nimish Shah, Wannes Meert, Marian Verhelst:
GRAPHOPT: constrained optimization-based parallelization of irregular graphs. CoRR abs/2105.01976 (2021) - [i12]Ehab M. Ibrahim, Linyan Mei, Marian Verhelst:
Survey and Benchmarking of Precision-Scalable MAC Arrays for Embedded DNN Processing. CoRR abs/2108.04773 (2021) - [i11]Nimish Shah, Laura Isabel Galindez Olascoaga, Shirui Zhao, Wannes Meert, Marian Verhelst:
DPU: DAG Processing Unit for Irregular Graphs with Precision-Scalable Posit Arithmetic in 28nm. CoRR abs/2112.05660 (2021) - 2020
- [j45]Juan Sebastian P. Giraldo, Steven Lauwereins, Komail M. H. Badami, Marian Verhelst:
Vocell: A 65-nm Speech-Triggered Wake-Up SoC for 10- $\mu$ W Keyword Spotting and Speaker Verification. IEEE J. Solid State Circuits 55(4): 868-878 (2020) - [j44]Athanasios T. Ramkaj, Juan Carlos Pena Ramos, Marcel J. M. Pelgrom, Michiel S. J. Steyaert, Marian Verhelst, Filip Tavernier:
A 5-GS/s 158.6-mW 9.4-ENOB Passive-Sampling Time-Interleaved Three-Stage Pipelined-SAR ADC With Analog-Digital Corrections in 28-nm CMOS. IEEE J. Solid State Circuits 55(6): 1553-1564 (2020) - [j43]Fernando de la Hucha Arce, Marc Moonen, Marian Verhelst, Alexander Bertrand:
Distributed adaptive node-specific signal estimation in a wireless sensor network with noisy links. Signal Process. 166 (2020) - [j42]Fernando de la Hucha Arce, Panagiotis Patrinos, Marian Verhelst, Alexander Bertrand:
On the Convexity of Bit Depth Allocation for Linear MMSE Estimation in Wireless Sensor Networks. IEEE Signal Process. Lett. 27: 291-295 (2020) - [j41]Leandro Mateus Giacomini Rocha, Dwaipayan Biswas, Bram-Ernst Verhoef, Sergio Bampi, Chris Van Hoof, Mario Konijnenburg, Marian Verhelst, Nick Van Helleputte:
Binary CorNET: Accelerator for HR Estimation From Wrist-PPG. IEEE Trans. Biomed. Circuits Syst. 14(4): 715-726 (2020) - [c97]Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst:
Acceleration of probabilistic reasoning through custom processor architecture. DATE 2020: 322-325 - [c96]Robby Neven, Marian Verhelst, Tinne Tuytelaars, Toon Goedemé:
Feed-Forward On-Edge Fine-Tuning Using Static Synthetic Gradient Modules. ECCV Workshops (5) 2020: 131-146 - [c95]Tom R. Molderez, Korneel Rabaey, Marian Verhelst:
An Affordable Multichannel Potentiostat with 128 Individual Stimulation and Sensing Channels. I2MTC 2020: 1-6 - [c94]Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Guy Van den Broeck, Marian Verhelst:
Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams. IDA 2020: 184-196 - [c93]Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Marian Verhelst:
Dynamic Complexity Tuning for Hardware-Aware Probabilistic Circuits. IoT Streams/ITEM@PKDD/ECML 2020: 283-295 - [i10]Colby R. Banbury, Vijay Janapa Reddi, Max Lam, William Fu, Amin Fazel, Jeremy Holleman, Xinyuan Huang, Robert Hurtado, David Kanter, Anton Lokhmotov, David A. Patterson, Danilo Pau, Jae-sun Seo, Jeff Sieracki, Urmish Thakker, Marian Verhelst, Poonam Yadav:
Benchmarking TinyML Systems: Challenges and Direction. CoRR abs/2003.04821 (2020) - [i9]Linyan Mei, Pouya Houshmand, Vikram Jain, Juan Sebastian P. Giraldo, Marian Verhelst:
ZigZag: A Memory-Centric Rapid DNN Accelerator Design Space Exploration Framework. CoRR abs/2007.11360 (2020) - [i8]Robby Neven, Marian Verhelst, Tinne Tuytelaars, Toon Goedemé:
Feed-Forward On-Edge Fine-tuning Using Static Synthetic Gradient Modules. CoRR abs/2009.09675 (2020)
2010 – 2019
- 2019
- [j40]Koen Goetschalckx, Marian Verhelst:
Breaking High-Resolution CNN Bandwidth Barriers With Enhanced Depth-First Execution. IEEE J. Emerg. Sel. Topics Circuits Syst. 9(2): 323-331 (2019) - [j39]Vincent Camus, Linyan Mei, Christian C. Enz, Marian Verhelst:
Review and Benchmarking of Precision-Scalable Multiply-Accumulate Unit Architectures for Embedded Neural-Network Processing. IEEE J. Emerg. Sel. Topics Circuits Syst. 9(4): 697-711 (2019) - [j38]Daniel Bankman, Lita Yang, Bert Moons, Marian Verhelst, Boris Murmann:
An Always-On 3.8 $\mu$ J/86% CIFAR-10 Mixed-Signal Binary CNN Processor With All Memory on Chip in 28-nm CMOS. IEEE J. Solid State Circuits 54(1): 158-172 (2019) - [j37]Thomas Bos, Wentao Jiang, Jan D'hooge, Marian Verhelst, Wim Dehaene:
Enabling Ultrasound In-Body Communication: FIR Channel Models and QAM Experiments. IEEE Trans. Biomed. Circuits Syst. 13(1): 135-144 (2019) - [j36]Tom R. Molderez, Xu Zhang, Korneel Rabaey, Marian Verhelst:
A Current-Driven Six-Channel Potentiostat for Rapid Performance Characterization of Microbial Electrolysis Cells. IEEE Trans. Instrum. Meas. 68(12): 4694-4702 (2019) - [j35]Massimo Alioto, Magdy S. Abadir, Tughrul Arslan, Chirn Chye Boon, Andreas Burg, Chip-Hong Chang, Meng-Fan Chang, Yao-Wen Chang, Poki Chen, Pasquale Corsonello, Paolo Crovetti, Shiro Dosho, Rolf Drechsler, Ibrahim Abe M. Elfadel, Ruonan Han, Masanori Hashimoto, Chun-Huat Heng, Deukhyoun Heo, Tsung-Yi Ho, Houman Homayoun, Yuh-Shyan Hwang, Ajay Joshi, Rajiv V. Joshi, Tanay Karnik, Chulwoo Kim, Tony Tae-Hyoung Kim, Jaydeep Kulkarni, Volkan Kursun, Yoonmyung Lee, Hai Helen Li, Huawei Li, Prabhat Mishra, Baker Mohammad, Mehran Mozaffari Kermani, Makoto Nagata, Koji Nii, Partha Pratim Pande, Bipul C. Paul, Vasilis F. Pavlidis, José Pineda de Gyvez, Ioannis Savidis, Patrick Schaumont, Fabio Sebastiano, Anirban Sengupta, Mingoo Seok, Mircea R. Stan, Mark M. Tehranipoor, Aida Todri-Sanial, Marian Verhelst, Valerio Vignoli, Xiaoqing Wen, Jiang Xu, Wei Zhang, Zhengya Zhang, Jun Zhou, Mark Zwolinski, Stacey Weber:
Editorial TVLSI Positioning - Continuing and Accelerating an Upward Trajectory. IEEE Trans. Very Large Scale Integr. Syst. 27(2): 253-280 (2019) - [c92]Linyan Mei, Mohit Dandekar, Dimitrios Rodopoulos, Jeremy Constantin, Peter Debacker, Rudy Lauwereins, Marian Verhelst:
Sub-Word Parallel Precision-Scalable MAC Engines for Efficient Embedded DNN Inference. AICAS 2019: 6-10 - [c91]Vincent Camus, Christian C. Enz, Marian Verhelst:
Survey of Precision-Scalable Multiply-Accumulate Units for Neural-Network Processing. AICAS 2019: 57-61 - [c90]Juan Sebastian P. Giraldo, Chris O'Connor, Marian Verhelst:
Efficient Keyword Spotting through Hardware-Aware Conditional Execution of Deep Neural Networks. AICCSA 2019: 1-8 - [c89]Thomas Bos, Wim Dehaene, Marian Verhelst:
Ultrasound In-Body Communication with OFDM through Multipath Realistic Channels. BioCAS 2019: 1-4 - [c88]Leandro Mateus Giacomini Rocha, Nick Van Helleputte, Muqing Liu, Dwaipayan Biswas, Bram-Ernst Verhoef, Sergio Bampi, Chris H. Kim, Chris Van Hoof, Mario Konijnenburg, Marian Verhelst:
Real-time HR Estimation from wrist PPG using Binary LSTMs. BioCAS 2019: 1-4 - [c87]Parvez Ahmmed, James Dieffenderfer, Jose Manuel Valero-Sarmiento, Venkata Rajesh Pamula, Nick Van Helleputte, Chris Van Hoof, Marian Verhelst, Alper Bozkurt:
A Wearable Wrist-Band with Compressive Sensing based Ultra-Low Power Photoplethysmography Readout Circuit. BSN 2019: 1-4 - [c86]Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst:
ProbLP: A framework for low-precision probabilistic inference. DAC 2019: 190 - [c85]Maxime Feyerick, Jaro De Roose, Marian Verhelst:
Exploration and Design of Low-Energy Logic Cells for 1 kHz Always-on Systems. DATE 2019: 1697-1702 - [c84]Peishuo Li, Tom R. Molderez, Frederik Ceyssens, Korneel Rabaey, Marian Verhelst:
A 64-channel, 1.1-pA-accurate On-chip Potentiostat for Parallel Electrochemical Monitoring. ESSCIRC 2019: 317-320 - [c83]Sander Smets, Toon Goedemé, Anurag Mittal, Marian Verhelst:
A 978GOPS/W Flexible Streaming Processor for Real-Time Image Processing Applications in 22nm FDSOI. ISSCC 2019: 44-46 - [c82]Athanasios Ramkaj, Juan Carlos Pena Ramos, Yifan Lyu, Maarten Strackx, Marcel J. M. Pelgrom, Michiel Steyaert, Marian Verhelst, Filip Tavernier:
A 5GS/s 158.6mW 12b Passive-Sampling 8×-Interleaved Hybrid ADC with 9.4 ENOB and 160.5dB FoMS in 28nm CMOS. ISSCC 2019: 62-64 - [c81]Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Guy Van den Broeck, Marian Verhelst:
On Hardware-Aware Probabilistic Frameworks for Resource Constrained Embedded Applications. EMC2@NeurIPS 2019: 66-70 - [c80]Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Marian Verhelst, Guy Van den Broeck:
Towards Hardware-Aware Tractable Learning of Probabilistic Models. NeurIPS 2019: 13726-13736 - [c79]Juan Sebastian P. Giraldo, Steven Lauwereins, Komail M. H. Badami, Hugo Van hamme, Marian Verhelst:
18μW SoC for near-microphone Keyword Spotting and Speaker Verification. VLSI Circuits 2019: 52- - 2018
- [j34]Laura Isabel Galindez Olascoaga, Komail M. H. Badami, Jonas Vlasselaer, Wannes Meert, Marian Verhelst:
Dynamic Sensor-Frontend Tuning for Resource Efficient Embedded Classification. IEEE J. Emerg. Sel. Topics Circuits Syst. 8(4): 858-872 (2018) - [j33]Koen Goetschalckx, Bert Moons, Steven Lauwereins, Martin Andraud, Marian Verhelst:
Optimized Hierarchical Cascaded Processing. IEEE J. Emerg. Sel. Topics Circuits Syst. 8(4): 884-894 (2018) - [j32]Juan Carlos Pena Ramos, Komail M. H. Badami, Steven Lauwereins, Marian Verhelst:
A Fully Configurable Non-Linear Mixed-Signal Interface for Multi-Sensor Analytics. IEEE J. Solid State Circuits 53(11): 3140-3149 (2018) - [j31]Chunshu Li, Yanxiang Huang, Khaled Khalaf, André Bourdoux, Marian Verhelst, Liesbet Van der Perre, Sofie Pollin:
Energy-Efficient Digital Front-End Processor for 60 GHz Polar Transmitter. J. Signal Process. Syst. 90(5): 777-789 (2018) - [c78]Bert Moons, Daniel Bankman, Lita Yang, Boris Murmann, Marian Verhelst:
BinarEye: An always-on energy-accuracy-scalable binary CNN processor with all memory on chip in 28nm CMOS. CICC 2018: 1-4 - [c77]Gage Hills, Daniel Bankman, Bert Moons, Lita Yang, Jake Hillard, Alex Kahng, Rebecca Park, Marian Verhelst, Boris Murmann, Max M. Shulaker, H.-S. Philip Wong, Subhasish Mitra:
TRIG: hardware accelerator for inference-based applications and experimental demonstration using carbon nanotube FETs. DAC 2018: 74:1-74:10 - [c76]Laura Isabel Galindez Olascoaga, Jonas Vlasselaer, Wannes Meert, Marian Verhelst:
Feature noise tuning for resource efficient Bayesian Network Classifiers. ESANN 2018 - [c75]Juan Sebastian P. Giraldo, Marian Verhelst:
Laika: A 5uW Programmable LSTM Accelerator for Always-on Keyword Spotting in 65nm CMOS. ESSCIRC 2018: 166-169 - [c74]Marian Verhelst:
Exploiting FDSOI Towards Minimum Energy Point Operation in Processors and Machine Learning Accelerators. ESSCIRC 2018: 217 - [c73]Jaro De Roose, Haoming Xin, Martin Andraud, Pieter J. A. Harpe, Marian Verhelst:
Flexible and Self-Adaptive Sense-and-Compress for Sub-MicroWatt Always-on Sensory Recording. ESSCIRC 2018: 282-285 - [c72]Marian Verhelst:
Exploiting FDSOI towards minimum energy point operation in processors and machine learning accelerators. ESSDERC 2018: 157 - [c71]Martin Andraud, Ahmed Hallawa, Jaro De Roose, Eugenio Cantatore, Gerd Ascheid, Marian Verhelst:
Evolving hardware instinctive behaviors in resource-scarce agent swarms exploring hard-to-reach environments. GECCO (Companion) 2018: 1497-1504 - [c70]Martin Andraud, Marian Verhelst:
From on-chip self-healing to self-adaptivity in analog/RF ICs: challenges and opportunities. IOLTS 2018: 131-134 - [c69]Lita Yang, Daniel Bankman, Bert Moons, Marian Verhelst, Boris Murmann:
Bit Error Tolerance of a CIFAR-10 Binarized Convolutional Neural Network Processor. ISCAS 2018: 1-5 - [c68]Daniel Bankman, Lita Yang, Bert Moons, Marian Verhelst, Boris Murmann:
An always-on 3.8μJ/86% CIFAR-10 mixed-signal binary CNN processor with all memory on chip in 28nm CMOS. ISSCC 2018: 222-224 - [c67]Komail M. H. Badami, Juan Carlos Pena Ramos, Steven Lauwereins, Marian Verhelst:
Mixed-signal programmable non-linear interface for resource-efficient multi-sensor analytics. ISSCC 2018: 344-346 - [c66]Martin Andraud, Laura Isabel Galindez Olascoaga, Yichuan Lu, Yiorgos Makris, Marian Verhelst:
On the use of Bayesian Networks for Resource-Efficient Self-Calibration of Analog/RF ICs. ITC 2018: 1-10 - [c65]Koen Goetschalckx, Bert Moons, Patrick Wambacq, Marian Verhelst:
Efficiently Combining SVD, Pruning, Clustering and Retraining for Enhanced Neural Network Compression. EMDL@MobiSys 2018: 1-6 - [c64]Jonas Vlasselaer, Wannes Meert, Marian Verhelst:
Towards Resource-Efficient Classifiers for Always-On Monitoring. ECML/PKDD (3) 2018: 305-321 - [c63]Komail M. H. Badami, Kushal Dakshina Murthy, Pieter Harpe, Marian Verhelst:
A 0.6V 54DB SNR Analog Frontend with 0.18% THD for Low Power Sensory Applications in 65NM CMOS. VLSI Circuits 2018: 241-242 - [i7]Matthijs Van Keirsbilck, Bert Moons, Marian Verhelst:
Resource aware design of a deep convolutional-recurrent neural network for speech recognition through audio-visual sensor fusion. CoRR abs/1803.04840 (2018) - [i6]Bert Moons, Daniel Bankman, Lita Yang, Boris Murmann, Marian Verhelst:
BinarEye: An Always-On Energy-Accuracy-Scalable Binary CNN Processor With All Memory On Chip in 28nm CMOS. CoRR abs/1804.05554 (2018) - [i5]Gert Dekkers, Fernando Rosas, Steven Lauwereins, Sreeraj Rajendran, Sofie Pollin, Bart Vanrumste, Toon van Waterschoot, Marian Verhelst, Peter Karsmakers:
A multi-layered energy consumption model for smart wireless acoustic sensor networks. CoRR abs/1812.06672 (2018) - 2017
- [j30]Yuri Murillo, Bertold Van den Bergh, Jona Beysens, Alexander Bertrand, Wim Dehaene, Panagiotis Patrinos, Tinne Tuytelaars, Ruth Vazquez Sabariego, Marian Verhelst, Patrick Wambacq, Sofie Pollin:
Multidisciplinary Learning through Implementation of the DVB-S2 Standard. IEEE Commun. Mag. 55(5): 124-130 (2017) - [j29]Bert Moons, Marian Verhelst:
An Energy-Efficient Precision-Scalable ConvNet Processor in 40-nm CMOS. IEEE J. Solid State Circuits 52(4): 903-914 (2017) - [j28]Venkata Rajesh Pamula, Jose Manuel Valero-Sarmiento, Long Yan, Alper Bozkurt, Chris Van Hoof, Nick Van Helleputte, Refet Firat Yazicioglu, Marian Verhelst:
A 172 µW Compressively Sampled Photoplethysmographic (PPG) Readout ASIC With Heart Rate Estimation Directly From Compressively Sampled Data. IEEE Trans. Biomed. Circuits Syst. 11(3): 487-496 (2017) - [j27]Juan Carlos Pena Ramos, Marian Verhelst:
Split-Delta Background Calibration for SAR ADCs. IEEE Trans. Circuits Syst. II Express Briefs 64-II(2): 221-225 (2017) - [j26]Fernando de la Hucha Arce, Marc Moonen, Marian Verhelst, Alexander Bertrand:
Adaptive Quantization for Multichannel Wiener Filter-Based Speech Enhancement in Wireless Acoustic Sensor Networks. Wirel. Commun. Mob. Comput. 2017 (2017) - [c62]Leonardo Cecconi, Sander Smets, Luca Benini, Marian Verhelst:
Optimal Tiling Strategy for Memory Bandwidth Reduction for CNNs. ACIVS 2017: 89-100 - [c61]Fernando Rosas, Konstantinos Manolakis, Christian Oberli, Mohammad Mahdi Azari, Marian Verhelst, Sofie Pollin:
Impact of interference correlation on the decoding error statistics. ACSSC 2017: 1115-1119 - [c60]Bert Moons, Koen Goetschalckx, Nick Van Berckelaer, Marian Verhelst:
Minimum energy quantized neural networks. ACSSC 2017: 1921-1925 - [c59]Martin Andraud, Gönenç Berkol, Jaro De Roose, Santosh Gannavarapu, Haoming Xin, Eugenio Cantatore, Pieter J. A. Harpe, Marian Verhelst, Peter G. M. Baltus:
Exploring the unknown through successive generations of low power and low resource versatile agents. DATE 2017: 290-293 - [c58]Bert Moons, Roel Uytterhoeven, Wim Dehaene, Marian Verhelst:
DVAFS: Trading computational accuracy for energy through dynamic-voltage-accuracy-frequency-scaling. DATE 2017: 488-493 - [c57]Gert Dekkers, Steven Lauwereins, Bart Thoen, Mulu Weldegebreal Adhana, Henk Brouckxon, Bertold Van den Bergh, Toon van Waterschoot, Bart Vanrumste, Marian Verhelst, Peter Karsmakers:
The SINS Database for Detection of Daily Activities in a Home Environment Using an Acoustic Sensor Network. DCASE 2017: 32-36 - [c56]Ahmed Hallawa, Jaro De Roose, Martin Andraud, Marian Verhelst, Gerd Ascheid:
Instinct-driven dynamic hardware reconfiguration: evolutionary algorithm optimized compression for autonomous sensory agents. GECCO (Companion) 2017: 1727-1734 - [c55]Tom R. Molderez, Bas de Wit, Korneel Rabaey, Marian Verhelst:
Successive parabolic interpolation as extremum seeking control for microbial fuel & electrolysis cells. IECON 2017: 3128-3133 - [c54]Bert Moons, Roel Uytterhoeven, Wim Dehaene, Marian Verhelst:
14.5 Envision: A 0.26-to-10TOPS/W subword-parallel dynamic-voltage-accuracy-frequency-scalable Convolutional Neural Network processor in 28nm FDSOI. ISSCC 2017: 246-247 - [c53]Meng-Fan Chang, Jun Deguchi, Vivek De, Masato Motomura, Shinichiro Shiratake, Marian Verhelst:
F3: Beyond the horizon of conventional computing: From deep learning to neuromorphic systems. ISSCC 2017: 506-508 - [c52]Thomas Bos, Komail M. H. Badami, Wim Dehaene, Marian Verhelst:
An 8-11b 320kS/s resolution scalable noise shaping SAR ADC. NEWCAS 2017: 209-212 - [i4]Bert Moons, Koen Goetschalckx, Nick Van Berckelaer, Marian Verhelst:
Minimum Energy Quantized Neural Networks. CoRR abs/1711.00215 (2017) - 2016
- [j25]Fernando Rosas, Vasilis Ntranos, Christopher J. Ellison, Sofie Pollin, Marian Verhelst:
Understanding Interdependency Through Complex Information Sharing. Entropy 18(2): 38 (2016) - [j24]Komail M. H. Badami, Steven Lauwereins, Wannes Meert, Marian Verhelst:
A 90 nm CMOS, 6µW Power-Proportional Acoustic Sensing Frontend for Voice Activity Detection. IEEE J. Solid State Circuits 51(1): 291-302 (2016) - [j23]Fernando de la Hucha Arce, Fernando Rosas, Marc Moonen, Marian Verhelst, Alexander Bertrand:
Generalized Signal Utility for LMMSE Signal Estimation With Application to Greedy Quantization in Wireless Sensor Networks. IEEE Signal Process. Lett. 23(9): 1202-1206 (2016) - [j22]Antti Anttonen, Adrian Kotelba, Marian Verhelst, Aarne Mämmelä:
Finite-Horizon Prediction of Energy Depletions in Off-Grid Wireless Networks. IEEE Trans. Veh. Technol. 65(8): 6731-6736 (2016) - [j21]Fernando Rosas, Richard Demo Souza, Marcelo Eduardo Pellenz, Christian Oberli, Glauber Gomes de Oliveira Brante, Marian Verhelst, Sofie Pollin:
Optimizing the Code Rate of Energy-Constrained Wireless Communications With HARQ. IEEE Trans. Wirel. Commun. 15(1): 191-205 (2016) - [c51]Laura Isabel Galindez Olascoaga, Komail M. H. Badami, V. Rajesh Pamula, Steven Lauwereins, Wannes Meert, Marian Verhelst:
Exploiting system configurability towards dynamic accuracy-power trade-offs in sensor front-ends. ACSSC 2016: 1027-1031 - [c50]V. Rajesh Pamula, Marian Verhelst, Chris Van Hoof, Refet Firat Yazicioglu:
A 17nA, 47.2dB dynamic range, adaptive sampling controller for online data rate reduction in low power ECG systems. BioCAS 2016: 272-275 - [c49]Tom Vermeulen, Fernando Rosas, Marian Verhelst, Sofie Pollin:
Performance analysis of in-band full duplex collision and interference detection in dense networks. CCNC 2016: 595-601 - [c48]