SOPC-Based Word Recognition System

Real-world processes generally produce observable outputs, which can be characterized as signals. The signals can be discrete in nature (e.g., characters from a finite alphabet, quantized vectors from a codebook), or continuous in nature (e.g., speech samples, temperature measurements, music). The signal source can be stationary (i.e., its statistical properties do not vary with time), or non-stationary (i.e., the signal properties vary over time). The signals can be pure (i.e., coming strictly from a single source), or can be corrupted from other signal sources (e.g., noise) or by transmission distortions, reverberation, etc.

Nios II Embedded Processor Design Contest―Outstanding Designs 2005




Second Prize


SOPC-Based Word Recognition System

Institution: National Institute Of Technology, Trichy

Participants: S. Venugopal, B. Murugan, S.V. Mohanasundaram

Instructor: Dr. B. Venkataramani




Design Introduction
Real-world processes generally produce observable outputs, which can be characterized as signals. The
signals can be discrete in nature (e.g., characters from a finite alphabet, quantized vectors from a
codebook), or continuous in nature (e.g., speech samples, temperature measurements, music). The
signal source can be stationary (i.e., its statistical properties do not vary with time), or non-stationary
(i.e., the signal properties vary over time). The signals can be pur