September 2018, Volume 8, Issue 3

Energy-Quality Scalable Circuits and Systems for Sensing and Computing: From Approximate to Communication-Inspired and Learning-Based
M. Alioto, V. De, and A. Marongiu

A MedRadio Receiver Front-End With Wide Energy-Quality Scalability Through Circuit and Architecture-Level Reconfigurations
G. Chang, S. Maity, B. Chatterjee, and S. Sen

A Quality-Configurable Approximate Serial Bus for Energy-Efficient Sensory Data Transfer
S. Behroozi, V. Raghunathan, A. Raghunathan, and Y. Kim

A Statistic-Based Scan Chain Reordering for Energy-Quality Scalable Scan Test
S. Seo, K. Cho, Y.-W. Lee, and S. Kang

Low-Power Approximate Multipliers Using Encoded Partial Products and Approximate Compressors
M. S. Ansari, H. Jiang, B. F. Cockburn, and J. Han

Significance-Driven Logic Compression for Energy-Efficient Multiplier Design
I. Qiqieh, R. Shafik, G. Tarawneh, D. Sokolov, S. Das, and A. Yakovlev

Optimal Selection of SRAM Bit-Cell Size for Power Reduction in Video Compression
H. Kim, I. J. Chang, and H.-J. Lee

An Accuracy/Energy-Flexible Configurable Gabor-Filter Chip Based on Stochastic Computation With Dynamic Voltage–Frequency–Length Scaling
N. Onizawa, D. Katagiri, K. Matsumiya, W. J. Gross, and T. Hanyu

An Energy-Efficient Online-Learning Stochastic Computational Deep Belief Network
Y. Liu, Y. Wang, F. Lombardi, and J. Han

Analog Approximate-FFT 8/16-Beam Algorithms, Architectures and CMOS Circuits for 5G Beamforming MIMO Transceivers
V. Ariyarathna, A. Madanayake, X. Tang, D. Coelho, R. J. Cintra, L. Belostotski, S. Mandal, and T. S. Rappaport

Energy and Reliability Improvement of Voltage-Based, Clustered, Coarse-Grain Reconfigurable Architectures by Employing Quality-Aware Mapping
H. Afzali-Kusha, O. Akbari, M. Kamal, and M. Pedram

An In-Memory VLSI Architecture for Convolutional Neural Networks
M. Kang, S. Lim, S. Gonugondla, and N. R. Shanbhag

A Spatial Multi-Bit Sub-1-V Time-Domain Matrix Multiplier Interface for Approximate Computing in 65-nm CMOS
S. Gopal, P. Agarwal, J. Baylon, L. Renaud, S. N. Ali, P. P. Pande, and D. Heo

OCEAN: An On-Chip Incremental-Learning Enhanced Artificial Neural Network Processor With Multiple Gated-Recurrent-Unit Accelerators
C. Chen, H. Ding, H. Peng, H. Zhu, Y. Wang, and C.-J. R. Shi

Exploring the Tradeoffs of Application-Specific Processing
J. C. Schabel and P. D. Franzon

A 2.2-µW Cognitive Always-On Wake-Up Circuit for Event-Driven Duty-Cycling of IoT Sensor Nodes
G. Rovere, S. Fateh, and L. Benini

A Neuro-Inspired Spike Pattern Classifier
P.-C. Huang and J. M. Rabaey

Design of a CMOS MEMS Accelerometer Used in IoT Devices for Seismic Detection
C.-T. Chiang

Content-Aware Low-Complexity Object Detection for Tracking Using Adaptive Compressed Sensing
J. W. Wells and A. Chatterjee

An Energy-Quality Scalable Wireless Image Sensor Node for Object-Based Video Surveillance
J. H. Ko, T. Na, and S. Mukhopadhyay

Complementary Detection for Hardware Efficient On-Site Monitoring of Parkinsonian Progress
A. Mohammed and A. Demosthenous

An Energy-Efficient and Reconfigurable Sensor IC for Bio-Impedance Spectroscopy and ECG Recording
J. Xu, P. Harpe, and C. Van Hoof

A Low-Power High-Speed Spintronics-Based Neuromorphic Computing System Using Real-Time Tracking Method
H. Farkhani, M. Tohidi, S. Farkhani, J. K. Madsen, and F. Moradi

Post-P&R Performance and Power Analysis for RRAM-Based FPGAs
X. Tang, E. Giacomin, G. De Micheli, and P.-E. Gaillardon