IMPLEMENTATION OF PERIODOGRAM SMOOTHING OF NOISYIMPLEMENTATION OF PERIODOGRAM SMOOTHING OF NOISY SIGNALS USING TMS320C6713 DSK
Periodogram Smoothing is a technique of power spectrum estimation. The discrete Fourier transform of a digital signal simply resolves the frequency components. The algorithm is implemented on Texas Instruments’ TMS320C6713 DSP Starter Kit (DSK). This is a 32-bit floating-point digital signal processor running at 225 MHz. The programs are basically written in the C programming language. However, those sections of code which are time-critical and memory-critical are written in assembly language of C6713. A MATLAB™ graphical user interface is also provided. The MATLAB™ program calls C programs loaded in Code Composer Studio (CCS). The C programs in turn call the assembly programs when required.
Summary
This master's thesis presents a practical implementation of periodogram smoothing for power spectral estimation and shows how to deploy it on a TI TMS320C6713 DSP board. The authors describe algorithmic choices, C and assembly optimizations for real-time performance, and a MATLAB GUI that interfaces with Code Composer Studio to run and visualize results.
Key Takeaways
- Understand the theory and practical steps of periodogram smoothing for noisy signals
- Implement FFT-based spectral estimation and smoothing on a TMS320C6713 using C and targeted assembly
- Optimize memory and compute-critical sections for real-time performance on a floating-point DSP
- Integrate DSP code with a MATLAB GUI via Code Composer Studio for interactive visualization
- Evaluate smoothing parameters and trade-offs (resolution vs. variance) for noisy-spectrum estimation
Who Should Read This
DSP engineers, graduate students, and embedded developers with experience in signal processing who want to implement and optimize power spectral estimation and real-time spectrum visualization on TI C6000 platforms.
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