606 research outputs found
Frontend em tempo real para cognitive radio inspirado na cóclea humana
Mestrado em Engenharia Electrónica e TelecomunicaçõesNesta tese vamos discutir a implementação e desenvolvimento de um frontend
inspirado na cóclea humana que é capaz de amostrar sinais RF com uma
larga largura de banda e gama dinâmica. Este front-end usa um multiplexer
de RF de 8 canais amostrado por uma placa com 8 ADCs a funcionar a
250MSPS. Uma placa de desenvolvimento com uma FPGA controla a ADC
e implementa os ltros de síntese digitais e liga a um computador pessoal
para transferir toda a informação e mudar os coe cientes dos ltros em
tempo real.In this thesis it will be discussed the real time implementation and development
of a front-end inspired by the Human Cochlea that is able to sample RF
signals with a large bandwidth and dynamic range. This front-end uses an 8
channel RF multiplexer sampled by an 8 channel 250MSPS ADC board. A
FPGA board controls the ADC, implements the digital synthesis lter bank
and connects to a personal computer to transfer the data and to change the
lters in real-time
Neuromorphic hardware for somatosensory neuroprostheses
In individuals with sensory-motor impairments, missing limb functions can be restored using neuroprosthetic devices that directly interface with the nervous system. However, restoring the natural tactile experience through electrical neural stimulation requires complex encoding strategies. Indeed, they are presently limited in effectively conveying or restoring tactile sensations by bandwidth constraints. Neuromorphic technology, which mimics the natural behavior of neurons and synapses, holds promise for replicating the encoding of natural touch, potentially informing neurostimulation design. In this perspective, we propose that incorporating neuromorphic technologies into neuroprostheses could be an effective approach for developing more natural human-machine interfaces, potentially leading to advancements in device performance, acceptability, and embeddability. We also highlight ongoing challenges and the required actions to facilitate the future integration of these advanced technologies
2022 roadmap on neuromorphic computing and engineering
Modern computation based on von Neumann architecture is now a mature cutting-edge science. In the von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This data transfer is responsible for a large part of the power consumption. The next generation computer technology is expected to solve problems at the exascale with 10 calculations each second. Even though these future computers will be incredibly powerful, if they are based on von Neumann type architectures, they will consume between 20 and 30 megawatts of power and will not have intrinsic physically built-in capabilities to learn or deal with complex data as our brain does. These needs can be addressed by neuromorphic computing systems which are inspired by the biological concepts of the human brain. This new generation of computers has the potential to be used for the storage and processing of large amounts of digital information with much lower power consumption than conventional processors. Among their potential future applications, an important niche is moving the control from data centers to edge devices. The aim of this roadmap is to present a snapshot of the present state of neuromorphic technology and provide an opinion on the challenges and opportunities that the future holds in the major areas of neuromorphic technology, namely materials, devices, neuromorphic circuits, neuromorphic algorithms, applications, and ethics. The roadmap is a collection of perspectives where leading researchers in the neuromorphic community provide their own view about the current state and the future challenges for each research area. We hope that this roadmap will be a useful resource by providing a concise yet comprehensive introduction to readers outside this field, for those who are just entering the field, as well as providing future perspectives for those who are well established in the neuromorphic computing community
Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 212
A bibliography listing 146 reports, articles, and other documents introduced into the NASA scientific and technical information system is presented. The subject coverage concentrates on the biological, psychological, and environmental factors involved in atmospheric and interplanetary flight. Related topics such as sanitary problems, pharmacology, toxicology, safety and survival, life support systems, and exobiology are also given attention
Bio-Inspired Compressive Sensing based on Auditory Neural Circuits for Real-time Monitoring and Control of Civil Structures using Resource Constrained Sensor Networks.
Recent natural hazard disasters including Hurricane Sandy (2012) and the Tohoku Earthquake (2011) have called public attention to the vulnerability of civil infrastructure systems. To enhance the resiliency of urban communities, arrays of wireless sensors and actuators have been proposed to monitor and control infrastructure systems in order to limit damage, speed emergency response, and make post-disaster decisions more efficiently. While great advances in the use of wireless sensor networks (WSNs) for the purposes of monitoring and control of civil infrastructure have been made, significant technological barriers have hindered their ability to be reliably used in the field for long durations. Some of these limitations include: reliance on finite, portable power supplies, limited radio bandwidth for data communication, and limited computational capacity. To resolve current bottlenecks, paradigm-altering approaches to the design of wireless monitoring and control systems are required. Through the process of evolution, biological central nervous systems (CNS) have evolved into highly adaptive and robust systems whose sensing and actuation capabilities far surpass the current capabilities of engineered (i.e., man-made) monitoring and control systems. In this dissertation, the mechanisms employed by biological sensory systems serve as sources of inspiration for overcoming the current challenges faced by wireless nodes for structural monitoring and control. The basic, yet elegant, methods of signal processing and data transmission used by the CNS are mimicked in this thesis to enable highly compressed communication with real-time data processing for WSNs engaged in infrastructure monitoring. Specifically, the parallelized time-frequency decomposition of the mammalian cochlea is studied, modeled, and recreated in an ultra-low power analog circuit. In lieu of transmitting data, the cochlea-inspired wireless sensors emulate the neurons by encoding filtered outputs into binary electrical spike trains for highly efficient wireless transmission. These transmitted spike train signals are processed for pattern classification of sensor data to identify structural damage and to perform feedback control in real-time. A key contribution of this thesis is the development and experimental validation of a bio-inspired wireless sensor node that exhibits large energy savings while employing real-time processing techniques, thus overcoming many of the current challenges of traditional wireless sensor nodes.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107302/1/cpeckens_1.pd
Multifaceted evaluation of a binaural cochlear‐ implant sound‐processing strategy inspired by the medial olivocochlear reflex
[ES]El objetivo de esta tesis es evaluar experimentalmente la audición de los usuarios de implantes cocleares con una estrategia de procesamiento binaural de sonidos inspirada en el reflejo olivococlear medial, denominada "estrategia MOC". La tesis describe cuatro estudios dirigidos a comparar la inteligibilidad del habla en ruido, la localización de fuentes sonoras y el esfuerzo auditivo con procesadores de sonido estándar y con diversos procesadores MOC diseñados para reflejar de forma más o menos realista el tiempo de activación del reflejo olivococlear medial natural y sus efectos sobre la comprensión coclear humana
Auf einem menschlichen Gehörmodell basierende Elektrodenstimulationsstrategie für Cochleaimplantate
Cochleaimplantate (CI), verbunden mit einer professionellen Rehabilitation,
haben mehreren hunderttausenden Hörgeschädigten die verbale Kommunikation
wieder ermöglicht. Betrachtet man jedoch die Rehabilitationserfolge, so
haben CI-Systeme inzwischen ihre Grenzen erreicht. Die Tatsache, dass die
meisten CI-Träger nicht in der Lage sind, Musik zu genießen oder einer
Konversation in geräuschvoller Umgebung zu folgen, zeigt, dass es noch Raum
für Verbesserungen gibt.Diese Dissertation stellt die neue
CI-Signalverarbeitungsstrategie Stimulation based on Auditory Modeling
(SAM) vor, die vollständig auf einem Computermodell des menschlichen
peripheren Hörsystems beruht.Im Rahmen der vorliegenden Arbeit wurde die
SAM Strategie dreifach evaluiert: mit vereinfachten Wahrnehmungsmodellen
von CI-Nutzern, mit fünf CI-Nutzern, und mit 27 Normalhörenden mittels
eines akustischen Modells der CI-Wahrnehmung. Die Evaluationsergebnisse
wurden stets mit Ergebnissen, die durch die Verwendung der Advanced
Combination Encoder (ACE) Strategie ermittelt wurden, verglichen. ACE
stellt die zurzeit verbreitetste Strategie dar. Erste Simulationen zeigten,
dass die Sprachverständlichkeit mit SAM genauso gut wie mit ACE ist.
Weiterhin lieferte SAM genauere binaurale Merkmale, was potentiell zu einer
Verbesserung der Schallquellenlokalisierungfähigkeit führen kann. Die
Simulationen zeigten ebenfalls einen erhöhten Anteil an zeitlichen
Pitchinformationen, welche von SAM bereitgestellt wurden. Die Ergebnisse
der nachfolgenden Pilotstudie mit fünf CI-Nutzern zeigten mehrere Vorteile
von SAM auf. Erstens war eine signifikante Verbesserung der
Tonhöhenunterscheidung bei Sinustönen und gesungenen Vokalen zu erkennen.
Zweitens bestätigten CI-Nutzer, die kontralateral mit einem Hörgerät
versorgt waren, eine natürlicheren Klangeindruck. Als ein sehr bedeutender
Vorteil stellte sich drittens heraus, dass sich alle Testpersonen in sehr
kurzer Zeit (ca. 10 bis 30 Minuten) an SAM gewöhnen konnten. Dies ist
besonders wichtig, da typischerweise Wochen oder Monate nötig sind. Tests
mit Normalhörenden lieferten weitere Nachweise für die verbesserte
Tonhöhenunterscheidung mit SAM.Obwohl SAM noch keine marktreife Alternative
ist, versucht sie den Weg für zukünftige Strategien, die auf Gehörmodellen
beruhen, zu ebnen und ist somit ein erfolgversprechender Kandidat für
weitere Forschungsarbeiten.Cochlear implants (CIs) combined with professional rehabilitation have
enabled several hundreds of thousands of hearing-impaired individuals to
re-enter the world of verbal communication. Though very successful, current
CI systems seem to have reached their peak potential. The fact that most
recipients claim not to enjoy listening to music and are not capable of
carrying on a conversation in noisy or reverberative environments shows
that there is still room for improvement.This dissertation presents a new
cochlear implant signal processing strategy called Stimulation based on
Auditory Modeling (SAM), which is completely based on a computational model
of the human peripheral auditory system.SAM has been evaluated through
simplified models of CI listeners, with five cochlear implant users, and
with 27 normal-hearing subjects using an acoustic model of CI perception.
Results have always been compared to those acquired using Advanced
Combination Encoder (ACE), which is today’s most prevalent CI strategy.
First simulations showed that speech intelligibility of CI users fitted
with SAM should be just as good as that of CI listeners fitted with ACE.
Furthermore, it has been shown that SAM provides more accurate binaural
cues, which can potentially enhance the sound source localization ability
of bilaterally fitted implantees. Simulations have also revealed an
increased amount of temporal pitch information provided by SAM. The
subsequent pilot study, which ran smoothly, revealed several benefits of
using SAM. First, there was a significant improvement in pitch
discrimination of pure tones and sung vowels. Second, CI users fitted with
a contralateral hearing aid reported a more natural sound of both speech
and music. Third, all subjects were accustomed to SAM in a very short
period of time (in the order of 10 to 30 minutes), which is particularly
important given that a successful CI strategy change typically takes weeks
to months. An additional test with 27 normal-hearing listeners using an
acoustic model of CI perception delivered further evidence for improved
pitch discrimination ability with SAM as compared to ACE.Although SAM is
not yet a market-ready alternative, it strives to pave the way for future
strategies based on auditory models and it is a promising candidate for
further research and investigation
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