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SSDCα – Inherently robust integrated biomimetic sensor-to-spike-to-digital converter based on peripheral neural ensembles

SSDCα – Ein inhärent robuster integrierter bioinspirierter Sensor-zu-Spike-nach-Digital-Wandler auf der Basis peripherer Neuronenstrukturen
Abhaya Chandra Kammara S.

Abhaya Chandra Kammara S. received the Bachelor's degree in Electronics & Instrumentation from the Anna University , Tamil Nadu India, in 2006. He worked as Assistant Systems Engineer TCS from Sept. 2006 to Aug. 2007 before he moved to TU Kaiserslautern, Germany. There he obtained the M.Sc. in Electrical Engineering at the Institute of Integrated Sensory Systems, TU Kaiserslautern, in 2010. He was appointed as research assistant at the same institute and is working towards his PhD in the field of innovative spiking sensor signal conditioning and conversion. His research interests are in mixed-signal circuit design & CAD, analog synthesis, hardware-software codesign, integrated intelligent sensor systems, ambient intelligence, smart sensing, smart kitchen, machine learning, spiking neural networks, and meta-heuristic optimization algorithms.

Institute of Integrated Sensor Systems, TU Kaiserslautern, Kaiserslautern, Germany

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and Andreas König

Andreas König received the Diploma in Electrical Engineering at TU Darmstadt in 1990 and the PhD at the Institute of Microelectronics Systems of the same university in 1995 in the field of intelligent vision system design for inspection tasks and of neural hardware. He then was with Fraunhofer IITB (now IOSB), in Karlsruhe continuing research in visual industrial inspection and aerial image analysis. He moved to TU Dresden, and from 1996 served as Assistant Prof. of Electronic Devices in the Electrical Engineering dept., and established a group in the field of integrated intelligent vision sensors, circuits, and systems design and application. In 2002, he was appointed deputy chair of the computer engineering chair, computer science dept. at TU Chemnitz. In 2003, he was appointed Prof. for Integrated Sensory Systems in the Electrical Engineering dept., TU Kaiserslautern. He established the Institute of Integrated Sensory Systems with research on heterogeneous integrated, intelligent multimodal sensor, circuit, and system design. Activities comprise reconfigurable or adaptive self-x systems, neural and evovable hardware, wireless, utonomous/self-sufficient sensors and sensor swarms or networks, CMOS and MEMS design and 3D integration, automation and synthesis activities, multidimensional signal processing and sensor fusion, and interactive large high-dimensional data analysis and visualization.

Institute of Integrated Sensor Systems, TU Kaiserslautern, Kaiserslautern, Germany

From the journal tm - Technisches Messen

Abstract

Rethinking analog to digital conversion has become extremely crucial in the race towards aggressively scaled technology nodes with decaying signal swings. The concept of more recent TDCs, which are completely designed in digital domain, make them simpler, easier to manufacture and faster to market. In previous work, LUCOS[1], a high dynamic range image sensor using spike based processing with high pixel uniformity had been designed. This motivated a generic ADC concept, which makes use of spike processing, to design a highly effective sensor signal processing system, which carries the promise of robustness to technology scaling, for effective use in IoT and Industrie 4.0. In this work, an ADC concept based on acoustic localization in biological sensory systems has been pursued. An ADC has been designed based on this concept using biological models of spiking neurons. The first proof-of-concept prototype chip SSDCα has been designed in ams 350 nm technology node with area of the chip is 8.5 mm2, sampling rate from DC to 150 kHz, resolution from 8-bit to 13-bit, with 28, 200 transistors, 263 neurons and 517 synapses. The future work will move from 350 nm to 90 nm technology node to show the improvement and robustness of the SSDC with technology scaling.

Zusammenfassung

Innovation in der Analog-Umwandlung hat eine entscheidende Bedeutung im Rennen hin zu aggressiv skalierten Technologien mit stark sinkenden Aussteuerbereichen gewonnen. Beispielsweise das in jüngerer Vergangenheit hinzugekommene Prinzip sogenannter TDCs, die nahezu vollständig in der digitalen Domäne realisiert sind, macht deren Realisierung strukturell einfacher, unempfindlicher und erleichtert die Herstellung. In Vorarbeiten wurde ein Bildsensor mit Spike-basierter Verarbeitung, hohem Dynamik- und Wertauflösungsbereich und sehr hoher Pixeluniformität entworfen (LUCOS). Diese Erfahrungen motivierten die Verfolgung eines generischen ADC-Konzepts, das die Verwendung von Spike-Verarbeitung nutzt, um eine höchsteffektive Sensorsignalverarbeitung zu erreichen, und verspricht robust hinsichtlich einer Technologieskalierung zu sein und damit eine Grundlage für den effektiven Einsatz integrierter Sensorelektronik in IoT und Industrie 4.0 zu bieten. In dieser Arbeit wurde konkret ein ADC-Konzept basierend auf akustischer Lokalisierung in biologischen Sinnessystemen verfolgt. Ein ADC wurde auf der Grundlage dieses Konzepts mit biologischen Modellen spikender Neuronen entworfen. Der erste Prototyp-Chip SSDCα zur Demonstration und Validierung des Ansatzes wurde in der ams 350 nm-Technologie entworfen, besitzt eine Fläche von 8.5 mm2, weist 28.200 Transistoren und 263 Neuronen mit 517 Synapsen auf, erlaubt eine Abtastrate von DC bis 150 kHz, und bietet eine Auflösung von 8 Bit bis 13 Bit. In künftiger Arbeit wird u. a. eine Skalierung des Entwurfs von 350 nm auf z. B. 90 nm-Technologie angestrebt, um die Vorteile und Robustheit des SSDC hinsichtlich Technologieskalierung zu belegen.

About the authors

Abhaya Chandra Kammara S.

Abhaya Chandra Kammara S. received the Bachelor's degree in Electronics & Instrumentation from the Anna University , Tamil Nadu India, in 2006. He worked as Assistant Systems Engineer TCS from Sept. 2006 to Aug. 2007 before he moved to TU Kaiserslautern, Germany. There he obtained the M.Sc. in Electrical Engineering at the Institute of Integrated Sensory Systems, TU Kaiserslautern, in 2010. He was appointed as research assistant at the same institute and is working towards his PhD in the field of innovative spiking sensor signal conditioning and conversion. His research interests are in mixed-signal circuit design & CAD, analog synthesis, hardware-software codesign, integrated intelligent sensor systems, ambient intelligence, smart sensing, smart kitchen, machine learning, spiking neural networks, and meta-heuristic optimization algorithms.

Institute of Integrated Sensor Systems, TU Kaiserslautern, Kaiserslautern, Germany

Andreas König

Andreas König received the Diploma in Electrical Engineering at TU Darmstadt in 1990 and the PhD at the Institute of Microelectronics Systems of the same university in 1995 in the field of intelligent vision system design for inspection tasks and of neural hardware. He then was with Fraunhofer IITB (now IOSB), in Karlsruhe continuing research in visual industrial inspection and aerial image analysis. He moved to TU Dresden, and from 1996 served as Assistant Prof. of Electronic Devices in the Electrical Engineering dept., and established a group in the field of integrated intelligent vision sensors, circuits, and systems design and application. In 2002, he was appointed deputy chair of the computer engineering chair, computer science dept. at TU Chemnitz. In 2003, he was appointed Prof. for Integrated Sensory Systems in the Electrical Engineering dept., TU Kaiserslautern. He established the Institute of Integrated Sensory Systems with research on heterogeneous integrated, intelligent multimodal sensor, circuit, and system design. Activities comprise reconfigurable or adaptive self-x systems, neural and evovable hardware, wireless, utonomous/self-sufficient sensors and sensor swarms or networks, CMOS and MEMS design and 3D integration, automation and synthesis activities, multidimensional signal processing and sensor fusion, and interactive large high-dimensional data analysis and visualization.

Institute of Integrated Sensor Systems, TU Kaiserslautern, Kaiserslautern, Germany

Received: 2015-12-4
Revised: 2016-7-12
Accepted: 2016-7-13
Published Online: 2016-9-13
Published in Print: 2016-9-28

©2016 Walter de Gruyter Berlin/Boston

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