r cells and give a weighted average of the potentials of the cells around it. Nearby cells are given the most weight and far cells less weight.(251) This technique is very important to this process because of the dynamic nature of image processing. If the image is accepted without testing its probable accuracy, the likelihood of image distortion would increase as the image changed. The silicon chip that the two professors developed contains about 2,500 pixels photoreceptors and their associated image-processing circuitry. The chip has circuitry that allows a professor to focus on each pixel individually or to observe the whole scene on a monitor. The professors stated in their paper, "The behavior of the adaptive retina is remarkably similar to that of biological systems" (qtd in Thompon 251). The retina was first tested by changing the light intensity of just one single pixel while the intensity of the surrounding cells was kept at a constant level. The design of the neural network caused the response of the surrounding pixels to react in the same manner as in biological retinas. They state that, "In digital systems, data and computational operations must be converted into binary code, a process that requires about 10,000 digital voltage changes per operation. Analog devices carry out the same operation in one step and so decrease the power consumption of silicon circuits by a factor of about 10,000" (qtd in Thompson 251). Besides validating their neural network, the accuracy of this silicon chip displays the usefulness of analog computing despite the assumption that only digital computing can provide the accuracy necessary for the processing of information. As close as these systems come to imitating their biological counterparts, they still have a long way to go. For a computer to identify more complex shapes, e. g., a persons face, the professors es...
