Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/139385
Title: A spiking neural network for pattern recognition
Authors: Nurin Atikah Bohari
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2020
Publisher: Nanyang Technological University
Project: A2018-191
Abstract: The human visual system is a sensory system that receives light and sends signals to the brain neurons to allow the person to see, recognize and distinguish objects and surroundings. Light exists as an electromagnetic radiation, where looking at different objects and surroundings will let the eye receive waves of different amplitude, frequency, and wavelength. The eye senses the light received and the light ray is refracted, where the light ray is bent as it enters from the air to the cornea to form an image. The light waves go through the cornea, pupil, and reaches the retina where the light energy is converted to neural activity. Similarly in biological systems, light sensing is used as a tool to process and classify objects. Pattern recognition is used in this simulation of light-sensing. Pattern recognition is the process of recognizing patterns by using a machine learning algorithm. It can be defined as the classification of data based on past knowledge or a statistical system extracted from patterns. Pattern recognition can be done on images, speeches, numeric data, and more.
URI: https://hdl.handle.net/10356/139385
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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