Title:
ELECTRONIC APPARATUS AND CONTROLLING METHOD THEREOF
Document Type and Number:
WIPO Patent Application WO/2020/036297
Kind Code:
A1
Abstract:
An electronic apparatus includes a storage configured to store a liquid-state machine (LSM) model and a recurrent neural networks (RNN) model, and a processor configured to input and process a feature data acquired from an input data using the LSM model, to input and process an output value output by the LSM model using the RNN model, and to identify whether a preset object is included in the input data based on an output value output by the RNN model. The RNN model is trained by a sample data related to the preset object. The LSM model includes a plurality of interlinked neurons. A weight applied to a link between the plurality of interlinked neurons is identified based on a spike at which a neuron value is greater than or equal to a preset threshold in a preset unit time.
Inventors:
USHAKOV YURY (KR)
Application Number:
PCT/KR2019/006880
Publication Date:
February 20, 2020
Filing Date:
June 07, 2019
Export Citation:
Assignee:
SAMSUNG ELECTRONICS CO LTD (KR)
International Classes:
G06N3/08; G06N3/04
Domestic Patent References:
| WO2017201511A1 | 2017-11-23 |
Foreign References:
| US5960391A | 1999-09-28 | |||
| US6601051B1 | 2003-07-29 | |||
| CN107464559A | 2017-12-12 |
Other References:
STEFAN KOK: "Liquid State Machine Optimization", MASTER'S THESIS, 2007, pages 1 - 82, XP055687305
ZHANG, YONG ET AL.: "A Digital Liquid State Machine With Biologically Inspired Learning and Its Application to Speech Recognition", IEEE TRANSACTIONS ON NEURAL NETWORK AND LEARNING SYSTEMS, vol. 26, no. 11, XP011586988, DOI: 10.1109/TNNLS.2015.2388544
ZHANG, YONG ET AL.: "A Digital Liquid State Machine With Biologically Inspired Learning and Its Application to Speech Recognition", IEEE TRANSACTIONS ON NEURAL NETWORK AND LEARNING SYSTEMS, vol. 26, no. 11, XP011586988, DOI: 10.1109/TNNLS.2015.2388544
Attorney, Agent or Firm:
KIM, Tae-hun et al. (KR)
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