Neural networks can be applied to the problem of extracting multipath delay information from the correlation of two signals. The ability of a feedforward neural network to learn the correct delay vector response is demonstrated using both broadband and narrowband correlation data. A trained neural network can be combined with a traditional adaptive algorithm for systems applications such as adaptive interference cancellation. In many cases, the network improves overall system performance by providing a nearly optimal starting point. The use of such an approach in an existing optical processing architecture is discussed.
SC176: Fractal and Wavelet Image Compression Techniques
Image compression techniques are an essential part of applications that operate across the Internet. This course examines the mathematics of fractal and wavelet image compression, with an emphasis on computer examples to illustrate the performance of different compression schemes. With the text, students will have access to the Windows software used in the course.
This course provides an introduction to the waveforms and signal processing techniques used in modern pulse radars. Emphasis will be on wideband waveforms. Discussion will include the role of both hardware and software in implementing the processing algorithms. Topics include: linear frequency modulated (LFM) waveforms; phase and frequency coded waveforms; pulse compression techniques; point spread function; doppler effects; ambiguity function; range resolution and bandwidth; waveform orthogonality and diversity; multiple-input, multiple-output (MIMO) processing; synthetic wideband techniques; range-doppler imaging. Examples from a high-fidelity simulation will illustrate the results.