analog integrated circuits

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A 16× Interleaved 32-GS/s 8b Hybrid ADC With Self-Tracking Inter-Stage Gain Achieving 44.3-dB SFDR at 20.9-GHz Input

A 16× Interleaved 32-GS/s 8b Hybrid ADC With Self-Tracking Inter-Stage Gain Achieving 44.3-dB SFDR at 20.9-GHz Input 150 150
Author(s): Hongzhi Liang, Jun Chang, Yixiao Luo, Li Dang, Haolin Han, Yi Shen, Dengquan Li, Shubin Liu, Ruixue Ding, Zhangming Zhu

Abstract:

This article presents a 32-GS/s 16-channel hierarchical time-interleaved (TI) hybrid analog-to-digital converter (ADC). The prototype utilizes the intrinsic high-speed quantization of time-domain (TD) ADC to reduce the interleaving factor. By incorporating hierarchical sampling and a cascode sampler, the compact TI-ADC achieves 44.3-dB spurious-free dynamic range (SFDR) at 20.9-GHz input. …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 11
Year of Publication: 2026
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2026.3680919
Publisher: IEEE

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High-Precision Close-to-Analog Programming of PCM Cells as Devices for AiMC Edge-AI

High-Precision Close-to-Analog Programming of PCM Cells as Devices for AiMC Edge-AI 150 150
Author(s): Alessio Antolini, Andrea Lico, Francesco Zavalloni, Lorenzo Greco, Riccardo Zurla, Jacopo Bertolini, Riccardo Vignali, Luca Iannelli, Emanuela Calvetti, Marco Pasotti, Alessandro Cabrini, Eleonora Franchi Scarselli

Abstract:

This article presents a high-precision close-to-analog programming methodology for phase-change memory (PCM) cells, targeting analog in-memory computing (AiMC) architectures for edge-artificial intelligence (AI) applications. By leveraging an iterative accumulation approach during the verify phase, the proposed technique enhances the effective number of bits (ENOBs) achievable in PCM cells. Experimental validation …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 14
Year of Publication: 2026
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2026.3680266
Publisher: IEEE

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PANNA: A 558 TOPS/W Pipelined All-Analog Neural Network Accelerator in 22 nm FD-SOI

PANNA: A 558 TOPS/W Pipelined All-Analog Neural Network Accelerator in 22 nm FD-SOI 150 150
Author(s): Jakob Finkbeiner, Raphael Nägele, Manuel Wittlinger, Markus Grözing, Manfred Berroth, Georg Rademacher

Abstract:

Analog computing offers intrinsic energy and latency benefits that makes it attractive for real-time and edge applications. Conventional analog accelerators suffer from repeated conversions between analog and digital domain, which degrades efficiency and throughput. We propose an all-analog pipelined neural network accelerator architecture in 22 nm fully-depleted silicon-on-insulator (FD-SOI) complementary metal-oxide-semiconductor (…

Published in: IEEE Solid-State Circuits Letters
Page(s): 365 – 368
Year of Publication: 2025
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2025.3627274
Publisher: IEEE

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