| CM-1K Neural Network Chip |
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CM-1K Neural Network Chip is a powerful neural network chip featuring 1024 neurons working in parallel and a parallel bus which allows to increase the network size by cascading multiple chips. It is an ideal companion chip for smart sensors and cameras and can classify patterns at high speed while coping with ill-defined data, the detection of unknown events, and adaptivity to changes of contexts and working conditions, etc. |
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In addition to its parallel neural network, CM-1K integrates a built-in recognition engine which can receive vector data directly from a sensor and broadcast it to the neurons in real-time. Upon receipt of the complete vector, the category of the firing neuron with the closest match is transmitted to the output bus. In the case of a monochrome video sensor, CogniMem offers a proprietary signature extraction from 2D video to 1D vector. The recognition engine can operate at sensor speed (up to 27 Mhz). The usage of the high-speed recognition engine requires that a knowledge be previously loaded into the neurons. |
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Features & Specifications |
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Patent parallel architecture |
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1024 parallel neurons |
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Vector data of up to 256 byte |
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10 ¦Ìs learning time (maximum) |
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10 ¦Ìs recognition time (maximum) |
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No limit to neuron expansion |
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Trained by example |
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Direct digital video recognition with CogniSight stage |
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RCE (Restricted Coulomb energy) |
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L1 and LSup distance norms |
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Radial Basis Function (RBF) or K-Nearest Neighbor (KNN) classifier |
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500 mW @ 15 MHz |
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3.3 V I/O operation 1.2 V core supply |
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100-pin TQFP package |
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0.13 ¦ÌM technology ¨C die size 8 x 8 mm |
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For more information, you can download some documentations from here. |
