Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 7 of 7 for “"sparse signal reconstruction"”.
-
A sparse signal reconstruction perspective for source localization with sensor arrays
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.
-
Identification of Interfering Signals in Software Defined Radio Applications Using Sparse Signal Reconstruction Techniques
… detecting the presence of interference in weak signal measurements. This thesis presents a new method for confirming the source of detected energy in weak signal measurements by sampling them directly, then estimating their expected effects. First, we assume that the detected signal is located …
-
Image reconstruction through polyfiltered variation minimization
<p>There has been considerable interest in reconstruction of remotely sensed imagery from incomplete frequency measurements for some time now. Given the nature of the collection process, it may be that portions of the spectrum are either missing or corrupted such that one is left with an incomplete …
-
Sparse spectrum fitting in array processing
… using sensor arrays. By developing the sparse representation models for the spatial covariance matrix of correlated or uncorrelated sources respectively, the DOA estimation problem is reformulated under the framework of Sparse Signal Reconstruction (SSR). The L1-Norm regularization …
-
Bayesian approaches to time-frequency inverse problems
… media such as gas, liquid or solid, audio signals are better defined and understood by the way their spectral composition evolves over time. Characterising the dynamics of these hidden spectral components—rather than their raw waveform—is crucial in a wide range of practical applications …
-
One-bit Compressed Sensing in the Presence of Noise
… data stressing the available computing and signal processing systems. In resource-constrained settings, it is desirable to process, store and transmit as little amount of data as possible. It has been shown that one can obtain acceptable performance for tasks such as inference and …
-
Real Time SLAM Using Compressed Occupancy Grids For a Low Cost Autonomous Underwater Vehicle
The research presented in this dissertation pertains to the development of a real time SLAM solution that can be performed by a low cost autonomous underwater vehicle equipped with low cost and memory constrained computing resources. The design of a custom rangefinder for underwater applications is …