کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
404130 677391 2013 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
The power of connectivity: Identity preserving transformations on visual streams in the spike domain
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
The power of connectivity: Identity preserving transformations on visual streams in the spike domain
چکیده انگلیسی

We investigate neural architectures for identity preserving transformations (IPTs) on visual stimuli in the spike domain. The stimuli are encoded with a population of spiking neurons; the resulting spikes are processed and finally decoded. A number of IPTs are demonstrated including faithful stimulus recovery, as well as simple transformations on the original visual stimulus such as translations, rotations and zoomings. We show that if the set of receptive fields satisfies certain symmetry properties, then IPTs can easily be realized and additionally, the same basic stimulus decoding algorithm can be employed to recover the transformed input stimulus. Using group theoretic methods we advance two different neural encoding architectures and discuss the realization of exact and approximate IPTs. These are realized in the spike domain processing block by a “switching matrix” that regulates the input/output connectivity between the stimulus encoding and decoding blocks. For example, for a particular connectivity setting of the switching matrix, the original stimulus is faithfully recovered. For other settings, translations, rotations and dilations (or combinations of these operations) of the original video stream are obtained. We evaluate our theoretical derivations through extensive simulations on natural video scenes, and discuss implications of our results on the problem of invariant object recognition in the spike domain.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neural Networks - Volume 44, August 2013, Pages 22–35
نویسندگان
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