Switching White Papers
Image Stream Processing on a Packet-Switched Discrete-Time CNN
Overview Cellular Neural Networks (CNNs) are widely used for real-time image processing applications. Though the Cellular Neural Network as a concept is characterized by a strict locality of operation, the large-scale digital implementation has been far from trivial. The intense interaction of a CNN node with all others within a specified neighbourhood poses severe interconnection requirements. Already 8 input and output values need to be communicated for the minimal 1-neighbourhood. The attached problem is the need for massively parallel and accumulated multiplications to implement the basic cell functionality. The earliest CNN realization was targeted on exploiting the benefits of analogue circuitry to handle high communication bandwidth requirements as well as dense footprint multiplication.
| Publisher | University of Groningen | File Format | |
|---|---|---|---|
| Date Published | February 2005 | ||
| Format | White Papers | ||
| Topics | |||
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