AER EAR: A Matched Silicon Cochlea Pair With Address Event Representation Interface

Chan, V.; Liu, Shih-Chii; Schaik, André van

doi:10.1109/tcsi.2006.887979

Cited by 244 publications

(141 citation statements)

References 25 publications

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“…An address-event encoder transmits the SGC circuits' spikes off-chip [39]- [41]. To communicate with the address-event encoder, the SGC makes a request when it spikes and clears this signal when acknowledged (see Req and Ack in Fig.…”

Section: B Spiral Ganglion Cell Circuitmentioning

confidence: 99%

A Silicon Cochlea With Active Coupling

Wen

Boahen

2009

IEEE Trans. Biomed. Circuits Syst.

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I. SILICON COCHLEAE SILICON (Si) cochleae emulate cochlear processing of sound stimuli in very-large scale integrated (VLSI) systems, attempting to match the biological cochlea's sound sensitivity, frequency selectivity, and dynamic range. The effort to build artificial cochleae in Si has been largely motivated by their potential applications in hearing aids, cochlear implants, and other portable devices that demand real-time, low-power signal processing for speech recognition; these requirements favor subthreshold analog VLSI designs [1]. Furthermore, analog VLSI is amenable to cochlea-like distributed processing due to its compact computational elements, large numbers of which can be integrated in a small area of Si. However, digital outputs are easier to interface with higher level processing, whether performed by other neuromorphic chips or implemented in computer software. Thus, a mixed-mode approach, where the cochlea's analog outputs are converted to digital pulses-a function performed by the auditory nerve (AN)-is most attractive.

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Section: B Spiral Ganglion Cell Circuitmentioning

confidence: 99%

A Silicon Cochlea With Active Coupling

Wen

Boahen

2009

IEEE Trans. Biomed. Circuits Syst.

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“…to implement log-polar or retinotopic mappings. Similarly events produced by other AER sensors, such as the silicon cochlea [5] can be used to create more complex saliency maps. Events produced from algorithms executed on workstations can also be used to shape or modulate the saliency map, for example to model the effect of top-down influences on the selective attention competitive process (see Section 3).…”

Section: The Active Vision Setupmentioning

confidence: 99%

A Real-Time Event-Based Selective Attention System for Active Vision

Sonnleithner

Indiveri

2012

Advances in Autonomous Mini Robots

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Abstract. In real world scenarios, guiding vision to focus on salient parts of the visual space is a computationally demanding tasks. Selective attention is a biologically inspired strategy to cope with this problem, that can be used in engineered systems with limited resources. In active vision systems however, the stringent realtime requirements limit the space of solutions that can be achieved with conventional machine vision techniques and systems. We propose a hybrid approach where we combine a custom neuromorphic VLSI saliency-map based attention system with a conventional machine vision system, to implement both fast contrast-based saccadic eye movements in parallel with conventional visual attention models that use high-resolution color input images. We describe the system and characterize its response properties with experiments using both basic control visual stimuli and natural scenes.

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“…In addition to such fundamental researches, many artificial electronic cochleae [12][13][14][15][16][17][18][19][20][21][22][23][24] have been also Synonyms of "asynchronous sequential logic" from some perspectives: Asynchronous sequential logic (hardware perspective) Asynchronous cellular automaton (dynamical system perspective) Asynchronous numerical integration (computation perspective) Asynchronous bifurcation processor (processor perspective) presented for clinical and engineering applications, e.g., cochlear implant [17][18][19][20][21][22][23] and cochlea-inspired sound processor for a mobile phone [24]. Concerning the electronic hardware, major hardware-oriented neural system modeling approaches include the following ones (see also Table I).…”

Section: Introductionmentioning

confidence: 99%

A novel cochlea partition model based on asynchronous bifurcation processor

Hironori

Izawa

Torikai

2015

NOLTA

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Abstract:The cochlea is a highly nonlinear biological sound processor the major components of which are lymph (viscous fluid), a basilar membrane (vibrating membrane in the viscous fluid), outer hair cells (active dumpers for the basilar membrane), inner hair cells (neural transducers), and spiral ganglion cells (parallel spikes density modulators). In this paper, a novel cochlea partition model based on a concept of an asynchronous bifurcation processor is presented. It is shown that the presented model can reproduce typical nonlinear responses of partitions of biological cochleae such as nonlinear DC response, nonlinear band-pass filtering, and adaptation. Also, FPGA experiments validate reproductions of these nonlinear responses.

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AER EAR: A Matched Silicon Cochlea Pair With Address Event Representation Interface

Cited by 244 publications

References 25 publications

A Silicon Cochlea With Active Coupling

A Silicon Cochlea With Active Coupling

A Real-Time Event-Based Selective Attention System for Active Vision

A novel cochlea partition model based on asynchronous bifurcation processor

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