本文選題：隨機(jī)匯池網(wǎng)絡(luò) + 平均互信息　； 參考：《青島大學(xué)》2017年碩士論文

【摘要】：本文主要以平均互信息量和刺激特定信息為評(píng)價(jià)指標(biāo),以確定性非周期信號(hào)和語音信號(hào)為輸入信號(hào),在Gamma噪聲和高斯噪聲存在的環(huán)境下,研究飽和性突觸型模型和積分發(fā)放型模型構(gòu)成的隨機(jī)匯池網(wǎng)絡(luò)的信號(hào)傳輸功能。在飽和型突觸神經(jīng)的隨機(jī)匯池網(wǎng)絡(luò)中,把非周期信號(hào)作為輸入的信號(hào),用Gamma噪聲模擬神經(jīng)元細(xì)胞群體的內(nèi)部噪聲,把平均互信息以及刺激特定信息作為衡量指標(biāo),分別對(duì)興奮性突觸神經(jīng)元構(gòu)成的同質(zhì)類隨機(jī)匯池網(wǎng)絡(luò),以及興奮性突觸神經(jīng)元與抑制性突觸神經(jīng)元共同構(gòu)成的異質(zhì)類隨機(jī)匯池網(wǎng)絡(luò)的隨機(jī)共振現(xiàn)象進(jìn)行了深入的研究,分析了網(wǎng)絡(luò)內(nèi)部的多種噪聲源給平均互信息與刺激特定信息帶來的變化;在積分發(fā)放神經(jīng)隨機(jī)匯池網(wǎng)絡(luò)中,采用語音信號(hào)作為輸入信號(hào),內(nèi)部噪聲為Gamma噪聲和高斯噪聲這兩種噪聲,同樣地,利用平均互信息和刺激特定信息評(píng)價(jià),觀察在積分發(fā)放神經(jīng)隨機(jī)匯池網(wǎng)絡(luò)中的隨機(jī)共振現(xiàn)象,分析改變?cè)肼晱?qiáng)度、積分發(fā)放神經(jīng)元并聯(lián)數(shù)目使隨機(jī)匯池網(wǎng)絡(luò)產(chǎn)生的信號(hào)傳遞效果;最后數(shù)值模擬結(jié)果表明,噪聲可以增強(qiáng)隨機(jī)匯池網(wǎng)絡(luò)中的輸入信號(hào)與輸出信號(hào)的平均互信息,而刺激特定信息量可以更加詳細(xì)地呈現(xiàn)出輸入信號(hào)中各個(gè)分量編碼的功效和神經(jīng)元內(nèi)部的噪聲可利用性。本課題的研究結(jié)論具有十分積極的影響,尤其對(duì)于今后處理神經(jīng)系統(tǒng)的信息具有一定的價(jià)值。
[Abstract]:In this paper, the average mutual information and specific stimulus information are taken as evaluation indexes, deterministic aperiodic signals and speech signals are used as input signals, and in the presence of Gamma noise and Gao Si noise, The signal transmission function of a random sink network composed of a saturated synaptic model and an integral distribution model is studied. In the random pool network of saturated synaptic nerve, the aperiodic signal is used as the input signal, the Gamma noise is used to simulate the internal noise of the neuronal cell population, and the average mutual information and the specific stimulation information are used as the measurement index. The Stochastic Resonance (SR) phenomena of the homogeneous random pool network formed by excitatory synaptic neurons and the heterogeneous random sink networks composed of excitatory synaptic neurons and inhibitory synaptic neurons were studied. The variation of average mutual information and stimulation specific information caused by various noise sources in the network is analyzed, and the speech signal is used as the input signal in the integral-distributed neural random sink network. The internal noise is Gamma noise and Gao Si noise. In the same way, using the mean mutual information and stimulating specific information evaluation, the stochastic resonance phenomenon in the integrated distributed neural stochastic sink network is observed, and the noise intensity is analyzed. The results of numerical simulation show that the noise can enhance the average mutual information between the input and output signals in the random sink network. Stimulation of specific amount of information can show in more detail the efficiency of each component of the input signal coding and the availability of noise inside the neuron. The conclusion of this study has a very positive effect, especially for the future processing of nervous system information.
【學(xué)位授予單位】：青島大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：R338

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