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ENEE222 — Elements of Discrete Signal Analysis

4 credits · 4 hours

Add to Personal Bookmarks Number of Identify the basic tools for signal analysis, such as real and complex sinusoids, sampling, linear transformations, and orthogonal projections. Explain the concepts of discrete and continuous time in signal analysis. Utilize the discrete Fourier transform (DFT) to analyze signals and introduce Fourier series. Break down the methodologies in linear time-invariant systems, including convolution (linear and circular), system functions, and frequency-selective filtering. Assess the effectiveness of FIR filters in signal processing. Develop a comprehensive understanding of signal analysis by integrating the discussed tools and methodologies. (Spring) Four hours lecture each week. Four Credits. Four billable hours. Course

Prerequisites: MATH136, CIS132

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