Samsung Electronics Co., Ltd.

Postech Academy-industry Foundation

Electronics and Telecommunications Research Institute

Seungjin Choi

Junho Lee

Jaein Kim

Huiwon Je

Jonggun Moon

Min Soo Kim

Jin-Woo Hong

Kyeongok Kang

Inseon Jang

Sun-Jae Lee

Jinwon Choi

Jae-Mo Sung

Hyukyeon Lee

Jiho Yoo

A method of operating a communication device includes: sweeping a plurality of first reception beams; measuring reference signals, received from another communication device, based on the plurality of first reception beams; estimating a downlink channel gain based on the measured reference signals and reception array response information corresponding to reception antenna characteristics of the communication device; generating a downlink channel related matrix based on the downlink channel gain and the reception array response information; determining a second reception beam based on the downlink channel related matrix; determining a transmission beam based on at least one of the downlink channel gain, the downlink channel related matrix, and the second reception beam; and performing communication with the other communication device using the second reception beam and the transmission beam.

Terminal performing beam sweeping operation and method of operation thereof

A method of performing beam training including obtaining at least one of a probability distribution and a value function for selecting one of a plurality of beams that are used to perform beamforming, selecting a candidate beam from among the plurality of beams based on the at least one of the probability distribution and the value function, the candidate beam being expected to be a best beam among the plurality of beams, performing a present training operation based on the candidate beam and a previous beam selected by at least one previous training operation, and selecting a better one of the candidate beam and the previous beam as a present beam based on a result of the present training operation may be provided.

Method of performing beam training based on reinforcement learning and wireless communication device performing the same

A user activity real-time recognition apparatus and method are provided and include a collector configured to collect a frequency-domain signal for each user activity and to generate learning data based on the frequency-domain signal. The apparatus and method also include an extractor configured to extract a user activity feature from the frequency-domain signal based on an activity feature extracting model. The activity feature extracting model is learned based on the learning data from the collector. The apparatus and method further include a classifier configured to analyze the user activity feature to classify a user activity pattern based on an activity pattern classifying model and configured to transmit the classified user activity pattern to an application device.

Apparatus and method for recognizing user activity

Provided is an apparatus of separating a musical sound source, which may re-construct mixed signals into target sound sources and other sound sources directly using sound source information performed using a predetermined musical instrument when the sound source information is present, thereby more effectively separating sound sources included in the mixed signal. The apparatus may include a Nonnegative Matrix Partial Co-Factorization (NMPCF) analysis unit to perform an NMPCF analysis on a mixed signal and a predetermined sound source signal using a sound source separation model, and to obtain a plurality of entity matrices based on the analysis result, and a target instrument signal separating unit to separate, from the mixed signal, a target instrument signal corresponding to the predetermined sound source signal by calculating an inner product between the plurality of entity matrices.

Method and system for separating musical sound source

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Pohang-si, South Korea

Seungjin Choi