Discrete-time signal processing (2nd ed.)
Discrete-time signal processing (2nd ed.)
Spikes: exploring the neural code
Spikes: exploring the neural code
Signals and Systems
Algorithms for designing wavelets to match a specified signal
IEEE Transactions on Signal Processing
Explicit parameterization of sleep EEG transients
Computers in Biology and Medicine
Computers in Biology and Medicine
Proceedings of the 2011 ACM Symposium on Applied Computing
Viewing by interactions: media-oriented operators for reviewing recorded sessions on tv
Proceddings of the 9th international interactive conference on Interactive television
Automatic authoring of interactive multimedia documents via media-oriented operators
ACM SIGAPP Applied Computing Review
Optimized orthonormal wavelet filters with improved frequency separation
Digital Signal Processing
Customization of wavelet function for pupil fluctuation analysis to evaluate levels of sleepiness
SITE'12 Proceedings of the 11th international conference on Telecommunications and Informatics, Proceedings of the 11th international conference on Signal Processing
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This work describes a new and different path to create a wavelet transform that can match a specified discrete-time signal. Called Spikelet, it is designed and optimized to spike and overlap pattern recognition in the digitalized signal that comes from H1, a motion-sensitive neuron of the fly's visual system. The technique proposed here and the associated algorithm, implemented in real time using a digital signal processor (DSP), are fully detailed. The results obtained matching the signal under analysis show an improvement over all other transforms, including the Daubechies transform. This reassures the efficacy of our transform. rm.