A new technique to construct a wavelet transform matching a specified signal with applications to digital, real time, spike, and overlap pattern recognition

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.