公开(公告)号：US11157798B2

公开(公告)日：2021-10-26

申请号：US15431606

申请日：2017-02-13

申请人： Brainchip, Inc.

发明人： Peter A J van der Made ,  Mouna Elkhatib ,  Nicolas Yvan Oros

IPC分类号： G06N3/04 ,  G06N3/08

摘要： Embodiments of the present invention provide an artificial neural network system for feature pattern extraction and output labeling. The system comprises a first spiking neural network and a second spiking neural network. The first spiking neural network is configured to autonomously learn complex, temporally overlapping features arising in an input pattern stream. Competitive learning is implemented as spike timing dependent plasticity with lateral inhibition in the first spiking neural network. The second spiking neural network is connected with the first spiking neural network through dynamic synapses, and is trained to interpret and label the output data of the first spiking neural network. Additionally, the labeled output of the second spiking neural network is transmitted to a computing device, such as a central processing unit for post processing.

公开(公告)号：US11151441B2

公开(公告)日：2021-10-19

申请号：US15428073

申请日：2017-02-08

申请人： Brainchip Inc.

发明人： Peter A J van der Made

IPC分类号： G06N3/04 ,  G06N3/063 ,  G06N3/08 ,  G06N20/00

摘要： Embodiments of the present invention provide an artificial neural network system for improved machine learning, feature pattern extraction and output labeling. The system comprises a first spiking neural network and a second spiking neural network. The first spiking neural network is configured to spontaneously learn complex, temporally overlapping features arising in an input pattern stream. Competitive learning is implemented as Spike Timing Dependent Plasticity with lateral inhibition in the first spiking neural network. The second spiking neural network is connected with the first spiking neural network through dynamic synapses, and is trained to interpret and label the output data of the first spiking neural network. Additionally, the output of the second spiking neural network is transmitted to a computing device, such as a CPU for post processing.

公开(公告)号：US10157629B2

公开(公告)日：2018-12-18

申请号：US15425861

申请日：2017-02-06

申请人： Brainchip Inc.

发明人： Peter A J van der Made ,  Mouna Elkhatib ,  Nicolas Yvan Oros

IPC分类号： G10L15/02 ,  G10L15/07 ,  G10L25/78 ,  G06N3/04 ,  G06N3/10 ,  G06F3/16 ,  G10L25/30 ,  G10L15/08

摘要： The present invention provides a system and method for controlling a device by recognizing voice commands through a spiking neural network. The system comprises a spiking neural adaptive processor receiving an input stream that is being forwarded from a microphone, a decimation filter and then an artificial cochlea. The spiking neural adaptive processor further comprises a first spiking neural network and a second spiking neural network. The first spiking neural network checks for voice activities in output spikes received from artificial cochlea. If any voice activity is detected, it activates the second spiking neural network and passes the output spike of the artificial cochlea to the second spiking neural network that is further configured to recognize spike patterns indicative of specific voice commands. If the first spiking neural network does not detect any voice activity, it halts the second spiking neural network.

公开(公告)号：US11429857B2

公开(公告)日：2022-08-30

申请号：US16282550

申请日：2019-02-22

申请人： BrainChip, Inc.

发明人： Peter A J van der Made ,  Anil Shamrao Mankar

IPC分类号： G06N3/08 ,  G06N20/00 ,  G06N3/04

摘要： Disclosed herein are system and method embodiments for establishing secure communication with a remote artificial intelligent device. An embodiment operates by capturing an auditory signal from an auditory source. The embodiment coverts the auditory signal into a plurality of pulses having a spatio-temporal distribution. The embodiment identifies an acoustic signature in the auditory signal based on the plurality of pulses using a spatio-temporal neural network. The embodiment modifies synaptic strengths in the spatio-temporal neural network in response to the identifying thereby causing the spatio-temporal neural network to learn to respond to the acoustic signature in the acoustic signal. The embodiment transmits the plurality of pulses to the remote artificial intelligent device over a communications channel thereby causing the remote artificial intelligent device to learn to respond to the acoustic signature, and thereby allowing secure communication to be established with the remote artificial intelligent device based on the auditory signature.

公开(公告)号：US10410117B2

公开(公告)日：2019-09-10

申请号：US14710593

申请日：2015-05-13

申请人： BrainChip, Inc.

发明人： Peter A J van der Made

IPC分类号： G06N3/08 ,  G06N3/04 ,  G06N3/06 ,  G06N3/063

摘要： A method for creating a dynamic neural function library that relates to Artificial Intelligence systems and devices is provided. Within a dynamic neural network (artificial intelligent device), a plurality of control values are autonomously generated during a learning process and thus stored in synaptic registers of the artificial intelligent device that represent a training model of a task or a function learned by the artificial intelligent device. Control Values include, but are not limited to, values that indicate the neurotransmitter level that is present in the synapse, the neurotransmitter type, the connectome, the neuromodulator sensitivity, and other synaptic, dendric delay and axonal delay parameters. These values form collectively a training model. Training models are stored in the dynamic neural function library of the artificial intelligent device. The artificial intelligent device copies the function library to an electronic data processing device memory that is reusable to train another artificial intelligent device.