Spiking Cochlea With System-Level Local Automatic Gain Control

Kiselev, Ilya; Gao, Chang; Liu, Shih-Chii

doi:10.1109/tcsi.2022.3150165

Cited by 10 publications

(6 citation statements)

References 51 publications

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“…Future work aims at developing adaptative capabilities in real time, as human ear does. Current research is focused on implementing a local automatic gain control [10] for input sound, and SBPF parameters (central pass frequency and Q factor) according to sound features performing an adaptation task in real time.…”

Section: Discussionmentioning

confidence: 99%

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Interfacing PDM MEMS Microphones with PFM Spiking Systems: Application for Neuromorphic Auditory Sensors

Jiménez-Fernández¹,

Gutiérrez-Galán

Ríos-Navarro³

et al. 2022

Neural Process Lett

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Neuromorphic computation processes sensors output in the spiking domain, which presents constraints in many cases when converting information to spikes, loosing, as example, temporal accuracy. This paper presents a spike-based system to adapt audio information from low-power pulse-density modulation (PDM) microelectromechanical systems microphones into rate coded spike frequencies. These spikes could be directly used by the neuromorphic auditory sensor (NAS) for frequency decomposition in different bands, avoiding the analog or digital conversion to spike streams. This improves the time response of the NAS, allowing its use in more time restrictive applications. This adaptation was conducted in VHDL as an interface for PDM microphones, converting their pulses into temporal distributed spikes following a pulse-frequency modulation scheme with an accurate inter-spike-interval, known as PDM to spikes interface (PSI). We introduce a new architecture of spike-based band-pass filter to reject DC components and distribute spikes in time. This was tested in two scenarios, first as a stand-alone circuit for its characterization, and then integrated with a NAS for verification. The PSI achieves a total harmonic distortion of $$-$$ - 46.18 dB and a signal-to-noise ratio of 63.47 dB, demands less than 1% of the resources of a Spartan-6 FPGA and its power consumption is around 7 mW.

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Section: Discussionmentioning

confidence: 99%

“…Currently, we can find diverse neuromorphic cochleae, both analog [6][7][8][9][10] and digital [11,12], inspired by Lyon's cascade model [13] modeling the Inner Hair Cells (IHC). In [14], a Neuromorphic Auditory Sensor (NAS) is presented, based on on spike signal processing (SSP) techniques [15].…”

Section: Introductionmentioning

confidence: 99%

Interfacing PDM MEMS Microphones with PFM Spiking Systems: Application for Neuromorphic Auditory Sensors

Jiménez-Fernández¹,

Gutiérrez-Galán

Ríos-Navarro³

et al. 2022

Neural Process Lett

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“…The proposed scheme is validated using a distribution network with multiple DG units. In [34], the researchers address the challenge of implementing local automatic gain control (AGC) circuitry in a silicon cochlea design. They propose an alternative system-level algorithm that incorporates channel-specific AGC by measuring the output spike activity of individual channels.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Complexity: Complexity indicates how intricate a control model is in terms of design and computational requirements. Work in [34] with its Spiking Cochlea with Local AGC model presents the lowest complexity ("Low") in this analysis. The Spiking Cochlea utilizes a straightforward mechanism for channel-specific automatic gain control.…”

Section: Empirical Analysismentioning

confidence: 99%

Comparative Analysis of Various Controllers used for Automatic Generation Control in Electrical Power Systems

2023

IJFMR

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In the rapidly evolving landscape of power systems, achieving a stable and efficient Automatic Generation Control (AGC) remains paramount. The exigency for this research stems from the critical role AGC plays in maintaining frequency and power balance amidst dynamic system changes. The consequences of inadequacies in AGC manifest as frequency deviations, system instabilities, and potential blackouts, with widespread socio-economic implications for different use cases. Historically, various controllers have been proposed and implemented to address AGC challenges. However, existing methodologies have displayed inherent limitations. Predominant issues include lack of adaptability to non-linearities, slow response times, inability to cater to the multifaceted nature of modern power grids with renewable integrations, and susceptibility to uncertainties and disturbances. This comprehensive review delves deep into the spectrum of controllers available for AGC, encompassing conventional PI/PID controllers, robust controllers, adaptive controllers, intelligent controllers, and the more recent forays into neural network-based and fuzzy logic controllers. Each controller's salient features, operational dynamics, advantages, and shortcomings are meticulously dissected. Furthermore, this paper elucidates the contexts in which each controller type excels or is found wanting, providing invaluable guidance for system designers and operators. In essence, this review serves as a holistic compass for stakeholders involved in power system operation and design. It offers both a retrospective understanding and prospective insights, assisting decision-makers in choosing the most suitable controller for a given scenario. Whether one aims to optimize AGC for a traditional grid, a grid with high renewable penetration, or a hybrid system, this paper promises to be an indispensable reference for researchers.

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“…For instance, the mirror pole in the OTA acts as a non-dominant pole thereby necessitating additional power dissipation to uphold the same bandwidth as in the SF filter. A parallel filter array adopting the XSF-based BPF was implemented in [41]; and was used in an environmental sound classification task [43] and a 2-class speech versus noise task [44] with an FPGA environment. D. Super Source-Follower (Second-Order LPF/BPF) Fig.…”

Section: Source-follower-based Filtersmentioning

confidence: 99%

Continuous-Time Analog Filters for Audio Edge Intelligence: Review and Analysis on Design Techniques

Kim¹,

Liu²

2022

Preprint

Self Cite

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Silicon cochlea designs capture the functionality of the biological cochlea. Their use has been explored for cochlea prosthesis applications and more recently in edge audio devices which are required to support always-on operation. As their stringent power constraints pose several design challenges, IC designers are forced to look for solutions that use low standby power. One promising bio-inspired approach is to combine the continuous-time analog filter channels of the silicon cochlea with a small memory footprint deep neural network that is trained on edge tasks such as keyword spotting, thereby allowing all blocks to be embedded in an IC. This paper reviews the analog filter circuits used as feature extractors for current edge audio devices, starting with the original biquad filter circuits proposed for the silicon cochlea. Our analysis starts from the interpretation of a basic biquad filter as a two-integrator-loop topology and reviews the progression in the design of second-order low-pass and band-pass filters ranging from OTA-based to source-followerbased architectures. We also derive and analyze the small-signal transfer function and discuss performance aspects of these filters. The analysis of these different filter configurations can be applied to other application domains such as biomedical devices which employ a front-end bandpass filter.

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Spiking Cochlea With System-Level Local Automatic Gain Control

Cited by 10 publications

References 51 publications

Interfacing PDM MEMS Microphones with PFM Spiking Systems: Application for Neuromorphic Auditory Sensors

Interfacing PDM MEMS Microphones with PFM Spiking Systems: Application for Neuromorphic Auditory Sensors

Comparative Analysis of Various Controllers used for Automatic Generation Control in Electrical Power Systems

Continuous-Time Analog Filters for Audio Edge Intelligence: Review and Analysis on Design Techniques

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