Capacity and energy cost of information in biological and silicon photoreceptors
Capacity and energy cost of information in biological and silicon photoreceptors
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DOI：
10.1109/5.939817
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发表时间：
2001-07-01
影响因子：
20.6
通讯作者：
Andreou, AG
中科院分区：
文献类型：
--
作者：
Abshire, P;Andreou, AG
我们概述了一个理论框架来分析生物感觉器官和工程微系统中的信息处理。我们采用通信理论的数学工具，并将自然或合成的物理结构建模为微尺度通信网络，在两个不同的抽象层次上在物理约束下研究它们。在职能层面，我们研究了业务和任务规范。而在物理层面上，我们研究的材料规格和实现。这两个抽象级别的特征在于确定为bi的香农信道容量、信道带宽、信号功率和噪声功率。通过用于信号上的变换、系统上的物理约束和使信号降级的噪声的模型来建立抽象的功能级别和物理级别之间的联系。我们提出了在生物和硅自适应光感受器中信息容量（比特每秒）与信息能量成本（焦耳每比特）的比较研究。两个系统中的每一个的通信信道模型是线性带限部分的级联，随后是加性噪声。我们的过滤器和噪声模型的第一原则，只要可能和现象学，否则。绿头苍蝇模型的参数确定从生物物理数据在文献中。硅模型的参数是从我们的实验数据确定的。这种比较研究是第一步，对系统性能和相关成本之间的权衡，如自然和工程传感微系统的尺寸，可靠性和能源需求的基本和定量的理解。
We outline a theoretical framework to analyze information processing in biological sensory organs and in engineered microsystems. We employ the mathematical tools of communication theory and model natural or synthetic physical structures as microscale communication networks, studying them under physical constraints at two different levels of abstraction. At the functional levels we examine the operational and task specification. while at the physical level, we examine the material specification and realization. Both levels of abstraction are characterized by Shannon's channel capacity as determined bi, the channel bandwidth, the signal power, and the noise power he link between the functional level and the physical level of abstraction is established through models for transformations on the signal, physical constraints on the system, and noise that degrades the signal.As a specific example, we present a comparative study of information capacity (in bits per second) versus energy cost of information (in joules per bit) in a biological and in a silicon adaptive photoreceptor The communication channel model for each of the two systems is a cascade of linear bandlimiting sections followed by additive noise. We model the filters and the noise from first principles whenever possible and phenomenologically otherwise. The parameters for the blowfly model are determined from biophysical data available in the literature. and the parameters of the silicon model are determined from our experimental data.This comparative study is a first step toward a fundamental and quantitative understanding of the tradeoffs between system performance and associated costs such as size, reliability, and energy requirements for natural and engineered sensory microsystems.