|Recognizes:||Signals, Images, Video|
|Number of neurochips:||4|
|Number of neurons:||2304|
|Vectors per second:||< 96 μsec|
|Max vector length:||256 Byte|
|FLASH memory:||Internal PC memory|
|Interfaces:||PCI Express X1 2.5 GT/s|
|Power Consumption:||<4 Watt|
|Dimensions (HxLxW):||8x120x68 mm|
Neuromorphic memory NT Adaptive PCIe series control boards have no microcontroller and can be mounted in any PC or other device with a PCIe connector. NT Adaptive PCIe boards come in three versions – with 4, 8 or 16 neural chips.
The opportunity of neuromorphic to identify the positions of circuit breakers, LEDs indicating real equipment is presented.
The program is developed on Python and combines various options for demonstrating the possibility of neuromorphic chips. Recognition of positions of automatic power supply units, light indication of control lamps, indications of dial gauges, values of seven-segment indicators, positions of biscuit switches.
The demo program written in Python is shown. This demo program uses a combination of the OpenCV open library and the CM1K chip (NM500) when working with the PCIe expansion board. OpenCV was used to search for faces in photographs, the training and recognition of the faces themselves was performed using neuromorphic chips.
Demonstration of the program developed on Python. Demonstration of the sequence of image selection, ROI selection, selection and tuning of parameters of a neuromorphic chip, such as MAXIF, categories, training and verification of learning outcomes. This program uses neuromorphic chips on a PCIe board.
The NT Adaptive PCIe is a fully parallel silicon neural network – it is a chain of identical elements (neurons) addressed in parallel and which have their own “genetic” material to learn and recall patterns without running a single line of code and without reporting to any supervising unit. In addition, the neurons fully collaborate with each other through a bi-directional and parallel neuron bus which is the key to accuracy, adaptivity and speed performance. Indeed, each neuron incorporates information from all the other neurons into its own learning logic and into its response logic.
Access to the network is through the PCIe interface.
Neural network key features
These operations are executed through API functions.
The content of each neuron is saved in 263 bytes as follows:
Vcc power supply 12 VDC
Total power up to 4 W
PCI Express X1 2.5 GT/s (PCI Express Base Specification, rev.2.1)
For installation in a 2U enclosure.
Dimension 120×68 mm.
Operating Temperature -40…+60 ℃
Storage Temperature -50… +80 ℃
NT Adaptive AI controllers identify various signals and makes programmed action.
NT Adaptive PCIe neural boards can recognize static and video images, sounds, various electrical signals, text, data.
Signal recognition process in neuromorphic chips takes place at the hardware level and makes huge acceleration for central processor. Controllers recognize signals in microseconds with only milliwats of power.
NT Adaptive PCIe board dimensions: 120x68x20 mm
NT Adaptive PCIe neural board panels can contain 2304, 4608 or even 9216 neurons.
Neural Network access takes place via the PCIe interface.