Advanced topics in signal processing
Natural object recognition
Learning object recognition strategies
Learning object recognition strategies
IPUS: an architecture for the integrated processing and understanding of signals
Artificial Intelligence
Data reprocessing in signal understanding systems
Data reprocessing in signal understanding systems
Prediction-driven computational auditory scene analysis
Prediction-driven computational auditory scene analysis
The complexity of perceptual search tasks
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
A goal-directed intermediate level executive for image interpretation
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
The role of data reprocessing in complex acoustic environments
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
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When dealing with signals from complex environments, where multiple time-dependent signal signatures can interfere with each other in stochastically unpredictable ways, traditional perceptual systems tend to fall back on a strategy of always performing finely-detailed, costly analysis of the signal with a comprehensive front end set of signal processing algorithms (SPAs), whether or not the current scenario requires the extra detail. Approximate SPAs (ASPAs) - algorithms whose processing time can be limited in order to trade off precision in their outputs for reduced execution time - can playa role in producing adaptive, less-costly front ends, but their outputs tend to require context-dependent analysis for use as evidence in interpretation. This paper examines the IPUS (Integrated Processing and Understanding of Signals) architecture's ability to serve as a support framework for applying ASPAs in interpretation problems. Specifically, our work shows that it is feasible to include an approximate version of the Short-Time Fourier Transform in an IPUS-based sound-understanding testbed.