A case for neuromorphic ISAs

Hashmi, Atif; Nere, Andrew; Thomas, James Jamal; Lipasti, Mikko H.

doi:10.1145/2248487.1950385

Cited by 4 publications

(1 citation statement)

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“…The model mimics aspects of the human visual cortex that recalls sequences stored hierarchically in an invariant. A mathematical formulation and a computational implementation of this model were further developed by Hashmi and Lipasti [13][14][15][16]. The model consists of an association of six-layered structures of different thickness constituted of a very large number of columns strongly connected via feed-forward and feedback connections.…”

Section: Primer On Cortical Algorithmsmentioning

confidence: 99%

Automated composer recognition for multi-voice piano compositions using rhythmic features, n-grams and modified cortical algorithms

Hajj

Filo

Awad

2017

Complex Intell. Syst.

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With the explosive growth of digital music data being stored and easily reachable on the cloud, as well as the increased interest in affective and cognitive computing, identifying composers based on their musical work is an interesting challenge for machine learning and artificial intelligence to explore. Capturing style and recognizing music composers have always been perceived reserved for trained musical ears. While there have been many researchers targeting music genre classification for improved recommendation systems and listener experience, few works have addressed automatic recognition of classical piano composers as proposed in this paper. This paper discusses the applicability of n-grams on MIDI music scores coupled with rhythmic features for feature extraction specifically of multi-voice scores. In addition, cortical algorithms (CA) are adapted to reduce the large feature set obtained as well as to efficiently identify composers in a supervised manner. When used to classify unknown composers and capture different styles, our proposed approach achieved a recognition rate of 94.4% on a home grown database of 1197 pieces with only 0.1% of the 231,542 generated features-which motivates follow-on research. The retained most significant features, indeed, provided interesting conclusions on capturing music style of piano composers. B Mariette Awad

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Section: Primer On Cortical Algorithmsmentioning

confidence: 99%

Automated composer recognition for multi-voice piano compositions using rhythmic features, n-grams and modified cortical algorithms

Hajj

Filo

Awad

2017

Complex Intell. Syst.

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On the role of astrocyte analog circuit in neural frequency adaptation

Ranjbar

Amiri

2015

Neural Comput & Applic

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An analog astrocyte–neuron interaction circuit for neuromorphic applications

Ranjbar

Amiri

2015

J Comput Electron

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Recent neurophysiologic findings have shown that astrocytes (the most abundant type of glial cells) are active partners in neural information processing and regulate the synaptic transmission dynamically. Motivated by these findings, in the present research, an analog neuromorphic circuit to study neuron-astrocyte signaling is presented. In this analog circuit, the firing dynamics of the neuron is described by Izhikevich neuron circuit and the Ca 2+ dynamics of a single astrocyte explained by a functional simplified model introduced by Montaseri et al. Using the proposed neuronastrocyte circuit, it is demonstrated that the proposed analog astrocyte is able to activate the analog neuron or change the neuron spiking frequency through bidirectional communication. This suggests that analog astrocyte is capable of modulating spike transmission frequency. Moreover, our results suggest that the analog circuit of neuron-astrocyte crosstalk produces diverse neural responses and therefore enhances the information processing capabilities of the neuromorphic circuits. This is suitable for applications in reconfigurable neuromorphic devices which implement biologically brain circuits.

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A case for neuromorphic ISAs

Cited by 4 publications

References 0 publications

Automated composer recognition for multi-voice piano compositions using rhythmic features, n-grams and modified cortical algorithms

Automated composer recognition for multi-voice piano compositions using rhythmic features, n-grams and modified cortical algorithms

On the role of astrocyte analog circuit in neural frequency adaptation

An analog astrocyte–neuron interaction circuit for neuromorphic applications

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