类蛋白质聚合体对声音的识别。

Recognition of sounds by ensembles of proteinoids.

作者信息

Mougkogiannis Panagiotis, Adamatzky Andrew

机构信息

Unconventional Computing Laboratory, UWE, Bristol, UK.

出版信息

Mater Today Bio. 2024 Feb 13;25:100989. doi: 10.1016/j.mtbio.2024.100989. eCollection 2024 Apr.

Abstract

Proteinoids are artificial polymers that imitate certain characteristics of natural proteins, including self-organization, catalytic activity, and responsiveness to external stimuli. This paper examines the acoustic response properties of proteinoids microspheres when exposed to auditory stimuli. We convert sounds of English alphabet into waveforms of electrical potential, feed the waveforms into proteinoid solutions and record electrical responses of the proteinoids. We also undertake a detailed comparison of proteinoids' electrical responses (frequencies, periods, and amplitudes) with original input signals. We found that responses of proteinoids are less regular, lower dominant frequency, wider distribution of proteinoids and less skewed distribution of amplitudes compared with input signals. We found that resonant acoustic excitation of proteinoids generates unique electrical impulse patterns dependent on sound frequency and amplitude. The finding will be used in further designs of organic electronic devices, based on ensembles of proteinoids, for sound processing and speech recognition. Our findings provide the first quantitative investigation into the potential of thermal proteinoid microspheres for bio-inspired sound processing and recognition applications. Using controlled speaker excitation on proteinoid samples, we create reliable markers of productive acoustic response capacities, paving the way for future advancement.

摘要

类蛋白是模仿天然蛋白质某些特性的人工聚合物,包括自组织、催化活性和对外部刺激的响应性。本文研究了类蛋白微球在受到听觉刺激时的声学响应特性。我们将英语字母的声音转换为电势波形,将这些波形输入类蛋白溶液并记录类蛋白的电响应。我们还对类蛋白的电响应(频率、周期和幅度)与原始输入信号进行了详细比较。我们发现,与输入信号相比,类蛋白的响应不太规则,主导频率较低,类蛋白分布更广泛,幅度分布的偏度较小。我们发现,类蛋白的共振声激发会产生依赖于声音频率和幅度的独特电脉冲模式。这一发现将用于基于类蛋白集合的有机电子设备的进一步设计,用于声音处理和语音识别。我们的研究结果首次对热类蛋白微球在受生物启发的声音处理和识别应用中的潜力进行了定量研究。通过对类蛋白样品使用受控扬声器激发,我们创建了可靠的有效声学响应能力标记,为未来的发展铺平了道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73e2/10879779/e25b9b628c96/ga1.jpg

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