# US 2025/0148263 A1 · Computer-implemented or hardware-implemented method of entity identification, a computer program product and an apparatus for entity identification > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2025/0148263 A1 - Document ID: US20250148263A1 - Status: Published application - Kind: A1 - Application number: 18/836,809 - Filed: 2023-02-08 - Published: 2025-05-08 - Earliest claimed: 2022-02-11 - Assignees: IntuiCell AB - Applicants: IntuiCell AB - Inventors: Henrik Jörntell; Linus Mårtensson - Web page: https://patentgrep.com/patent/US20250148263A1 ## CPC - G06N 3/044: Recurrent networks, e.g. Hopfield networks - G06N 3/045: Combinations of networks - G06N 3/0464: Convolutional networks [CNN, ConvNet] - G06N 3/049: Temporal neural networks, e.g. delay elements, oscillating neurons or pulsed inputs - G06N 3/092: Reinforcement learning - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract The disclosure relates to a data processing system (100), configured to have one or more system input(s) (110a, 110b, . . . , 110z) comprising data to be processed and a system output (120), comprising: a first network, NW, (130) comprising a plurality of first nodes (130a, 130b, . . . , 130x), each first node configured to have a plurality of inputs (132a, 132b, . . . , 132y), at least one of the plurality of inputs being a system input, and configured to produce an output (134a, 134b, . . . , 134x); a second NW (140) comprising first and second sets (146, 148) of second nodes (140a, 140b, . . . , 140u), each second node being configured to have an output (134a, 134b, . . . , 134x) of one or more first nodes (130a, 130b, . . . , 130x) as input(s) (142a, 142b, . . . , 142u) and configured to produce an output (144a, 144b, . . . , 144u), wherein the system output (120) comprises the outputs (134a, 134b, . . . , 134x) of each first node (130a, 130b, . . . , 130x); and wherein the output (144a) of a second node (140a) of the first set (146) of nodes (140a) is utilized as an input to one or more processing units (136a3, 136b1), each processing unit (136a3, 136b1) being configured to provide negative feedback to a respective first node (130a, 130b); and/or wherein the output (144) of a second node (140u) of the second set (148) of nodes (140b, . . . , 140u) is utilized as an input to one or more processing units (136x3), each processing unit being configured to provide positive feedback to a respective first node (130x). The disclosure further relates to a second NW, a method, and a computer program product. ## Claims ### Claim 1 A data processing system (100), configured to have one or more system input(s) (110a, 110b, . . . , 110z) comprising data to be processed and a system output (120), comprising: a first network, (130) comprising a plurality of first nodes (130a, 130b, . . . , 130x), each first node configured to have a plurality of inputs (132a, 132b, . . . , 132y), at least one of the plurality of inputs being a system input, and configured to produce an output (134a, 134b, . . . , 134x); a second network (140) comprising first and second sets (146, 148) of second nodes (140a, 140b, . . . , 140u), each second node being configured to have an output (134a, 134b, . . . , 134x) of one or more first nodes (130a, 130b, . . . , 130x) as input(s) (142a, 142b, . . . , 142u) and configured to produce an output (144a, 144b, . . . , 144u); wherein the system output (120) comprises the outputs (134a, 134b, . . . , 134x) of each first node (130a, 130b, . . . , 130x); and wherein the output (144a) of a second node (140a) of the first set (146) of nodes (140a) is utilized as an input to one or more processing units (136a3, 136b1), each processing unit (136a3, 136b1) being configured to provide negative feedback to a respective first node (130a, 130b), and/or wherein the output (144) of a second node (140u) of the second set (148) of nodes (140b, . . . , 140u) is utilized as an input to one or more processing units (136x3), each processing unit being configured to provide positive feedback to a respective first node (130x). ### Claim 2 (depends on 1) The data processing system of claim 1, wherein each of the plurality of first nodes (130a, 130b, . . . , 130x) comprises a processing unit (136a1, 136a2, . . . , 136x3) for each of the plurality of inputs (132a, 132b, . . . , 132y), wherein each processing unit (136a1, 136a2, . . . , 136x3) comprises an amplifier and a leaky integrator having a time constant (A1, A2), and wherein the time constant (A1) for processing units (136a3, . . . , 136x3) having the output of a node of the first or second sets (146, 148) of nodes (140a, . . . , 140u) as an input is larger, than the time constant (A2) for other processing units. ### Claim 3 (depends on 1) The data processing system of claim 1, wherein the output (144a, 144b, . . . , 144u) of each node of the first and/or second sets of nodes (146, 148) is inhibited while the data processing system (100) is in a learning mode. ### Claim 4 (depends on 1) The data processing system of claim 1, wherein each processing unit comprises an inhibiting unit configured to inhibit the output (144a, 144b, . . . , 144u) of each node of the first and/or second sets of nodes (146, 148) while the data processing system is in the learning mode. ### Claim 5 (depends on 1) The data processing system of claim 1, wherein each node (140a, 140b, . . . , 140u) of the first and second sets of nodes (146, 148) comprises an enabling unit, wherein each enabling unit is directly connected to the output (144a, 144b, . . . , 144u) of the respective node (140a, 140b, . . . , 140u), and wherein the enabling unit(s) is configured to inhibit the output (144a, 144b, . . . , 144u) while the data processing system is in the learning mode. ### Claim 6 (depends on 3) The data processing system of claim 3, wherein the data processing system (100) comprises a comparing unit (150), and wherein the comparing unit (150) is configured to compare the system output (140) to an adaptive threshold while the data processing system (100) is in the learning mode, and wherein the output (144a, . . . , 144u) of each node (140a, 140b, . . . , 140u) of the first or second sets of nodes (146, 148) is inhibited only when the system output (140) is larger than the adaptive threshold. ### Claim 7 (depends on 1) The data processing system of claim 1, wherein the system input(s) comprises sensor data of a plurality of contexts/tasks. ### Claim 8 (depends on 1) The data processing system of claim 1, wherein the data processing system is configured to from the sensor data learn to identify one or more entities while in a learning mode and thereafter configured to identify the one or more entities while in a performance mode and wherein the identified entity is one or more of a speaker, a spoken letter, syllable, phoneme, word or phrase present in the sensor data or an object or a feature of an object present in sensor data or a new contact event, an end of a contact event, a gesture or an applied pressure present in the sensor data. ### Claim 9 (depends on 1) The data processing system of claim 1, wherein each input (142a, 142b, . . . , 142u) of the second nodes (140a, 140b, . . . , 140u) is a weighted version of an output (134a, 134b, . . . , 134x) of the one or more first nodes (130a, 130b, . . . , 130x). ### Claim 10 (depends on 3) The data processing system of claim 3, wherein learning while in the learning mode and/or updating of weights for the first and/or the second networks (130, 140) is based on correlation. ### Claim 11 A second network, (140) connectable to a first network (130), the first network (130) comprising a plurality of first nodes (130a, 130b, . . . , 130x), each first node (130a, 130b, . . . , 130x) configured to have a plurality of inputs (132a, 132b, . . . , 132x), configured to produce an output (134a, 134b, . . . , 134x) and comprising at least one processing unit 136a3, . . . , 136x3, the second network (140) comprising; first and second sets (146, 148) of second nodes (140a, 140b, . . . , 140u), each second node (140a, 140b, . . . , 140u) being configurable to have an output (134a, 134b, . . . , 134x) of one or more first nodes (130a, 130b, . . . , 130x) as input(s) (142a, 142b, . . . , 142u) and configured to produce an output (144a, 144b, . . . , 144u); and wherein the output (144a) of a second node (140a) of the first set (146) of nodes (140a) is utilizable as an input to one or more processing units (136a3, 136b1), each processing unit (136a3, 136b1) being configured to provide negative feedback to a respective first node (130a, 130b), and/or wherein the output (144u) of a second node (140u) of the second set (148) of nodes (140b, . . . , 140u) is utilizable as an input to one or more processing units (136x3), each processing unit being configured to provide positive feedback to a respective first node (130x). ### Claim 12 A computer-implemented or hardware-implemented method (300) for processing data, comprising: receiving (310) one or more system input(s) (110a, 110b, . . . , 110z) comprising data to be processed; providing (320) a plurality of inputs (132a, 132b, . . . , 132y), at least one of the plurality of inputs being a system input, to a first network, (130) comprising a plurality of first nodes (130a, 130b, . . . , 130x); receiving (330) an output (134a, 134b, . . . , 134x) from each first node (130a, 130b, 130x); providing (340) a system output (120), comprising the output (134a, 134b, . . . , 134x) of each first node (130a, 130b, . . . , 130x); providing (350) the output (134a, 134b, . . . , 134x) of each first node (130a, 130b, . . . , 130x) to a second network (140) comprising first and second sets (146, 148) of second nodes (140a, 140b, . . . , 140u); receiving (360) output (144a, 144b, . . . , 144u) of each second nodes (140a, 140b, . . . , 140u); and utilizing (370) the output (144a) of a second node (140a) of the first set (146) of nodes (140a) as an input to one or more processing units (136a3, 136b1), each processing unit (136a3, 136b1) being configured to provide negative feedback to a respective first node (130a, 130b); and/or utilizing (380) the output (144) of a second node (140u) of the second set (148) of nodes (140b, . . . , 140u) as an input to one or more processing units (136x3), each processing unit (136x3) being configured to provide positive feedback to a respective first node (130x). ### Claim 13 (depends on 1) A computer program product comprising a non-transitory computer readable medium (400), having stored thereon a computer program comprising program instructions, the computer program being loadable into a data processing unit (420) and configured to cause execution of the method according to claim 1 when the computer program is run by the data processing unit (420).