Proteinoid-polyaniline neuromorphic composites for audio recognition

Abstract We present an innovative neuromorphic system using a proteinoid-polyaniline (PANI) composite for recognition of audio inputs of the English alphabet. Neuromorphic devices, which draw inspiration from the neural networks of the brain, have emerged as very promising potential solutions for efficient signal processing. The proteinoid-PANI composite was synthesized through a template-free method, resulting in a unique nanostructure consisting of both nanorods and nanospheres. Principal component analysis, spectrogram analysis, and temporal spiking response analysis were among the signal processing methods used to examine the composite’s audio response to English alphabet stimuli. The system showed a moderate positive correlation between input and output signals, unique time–frequency response patterns, and convoluted spiking behaviour. In addition, the output amplitude showed less variation compared to the input, while maintaining the same temporal characteristics. Microscopic analysis provided detailed information about the morphology of the composite. The nanorods displayed an optimal aspect ratio and had diameters of around 100 nm, while the nanospheres varied in size, ranging from 200 to 500 nm in diameter. The nanostructure, morphological characteristics, and signal processing properties of the proteinoid-PANI composite demonstrate its potential for advanced applications in neuromorphic computing and signal processing, particularly in speech recognition and human–machine interaction.

Authors

Institutions

Publication Details

Journal
Smart Materials and Structures
Published
2024-12-18
DOI
https://doi.org/10.1088/1361-665x/ada0ff
Citations
4
Primary Topic
Conducting polymers and applications
Type
article
Field-Weighted Citation Impact
0.67

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Proteinoid-polyaniline neuromorphic composites for audio recognition

Andrew Adamatzky, Panagiotis Mougkogiannis
4 citations
Smart Materials and Structures
Conducting polymers and applications
0.67
article

Proteinoid-polyaniline neuromorphic composites for audio recognition

Andrew Adamatzky, Panagiotis Mougkogiannis
article en
4 citations

Abstract

Abstract We present an innovative neuromorphic system using a proteinoid-polyaniline (PANI) composite for recognition of audio inputs of the English alphabet. Neuromorphic devices, which draw inspiration from the neural networks of the brain, have emerged as very promising potential solutions for efficient signal processing. The proteinoid-PANI composite was synthesized through a template-free method, resulting in a unique nanostructure consisting of both nanorods and nanospheres. Principal component analysis, spectrogram analysis, and temporal spiking response analysis were among the signal processing methods used to examine the composite’s audio response to English alphabet stimuli. The system showed a moderate positive correlation between input and output signals, unique time–frequency response patterns, and convoluted spiking behaviour. In addition, the output amplitude showed less variation compared to the input, while maintaining the same temporal characteristics. Microscopic analysis provided detailed information about the morphology of the composite. The nanorods displayed an optimal aspect ratio and had diameters of around 100 nm, while the nanospheres varied in size, ranging from 200 to 500 nm in diameter. The nanostructure, morphological characteristics, and signal processing properties of the proteinoid-PANI composite demonstrate its potential for advanced applications in neuromorphic computing and signal processing, particularly in speech recognition and human–machine interaction.

Smart Materials and StructuresVol. 34(1)
University of the West of England (GB)
Engineering and Physical Sciences Research Council
Quality Education
Openalex Percentile: Top 36%
Conducting polymers and applications
0.67
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Proteinoid-polyaniline neuromorphic composites for audio recognition — Andrew Adamatzky, Panagiotis Mougkogiannis · Smart Materials and Structures (2024) | TGRS Research Map | TGRS