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公开(公告)号：US20230006611A1
公开(公告)日：2023-01-05
申请号：US17857132
申请日：2022-07-04
Applicant: MediaTek Inc.
Inventor： Po-Yu Chen , Hao Chen , Yi-Min Tsai , Hao Yun Chen , Hsien-Kai Kuo , Hantao Huang , Hsin-Hung Chen , Yu Hsien Chang , Yu-Ming Lai , Lin Sen Wang , Chi-Tsan Chen , Sheng-Hong Yan
Abstract: A compensator compensates for the distortions of a power amplifier circuit. A power amplifier neural network (PAN) is trained to model the power amplifier circuit using pre-determined input and output signal pairs that characterize the power amplifier circuit. Then a compensator is trained to pre-distort a signal received by the PAN. The compensator uses a neural network trained to optimize a loss between a compensator input and a PAN output, and the loss is calculated according to a multi-objective loss function that includes one or more time-domain loss function and one or more frequency-domain loss functions. The trained compensator performs signal compensation to thereby output a pre-distorted signal to the power amplifier circuit.
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公开(公告)号：US20230064692A1
公开(公告)日：2023-03-02
申请号：US17846007
申请日：2022-06-22
Applicant: MediaTek Inc.
Inventor： Hao Yun Chen , Min-Hung Chen , Min-Fong Horng , Yu-Syuan Xu , Hsien-Kai Kuo , Yi-Min Tsai
Abstract: According to a network space search method, an expanded search space is partitioned into multiple network spaces. Each network space includes a plurality of network architectures and is characterized by a first range of network depths and a second range of network widths. The performance of the network spaces is evaluated by sampling respective network architectures with respect to a multi-objective loss function. The evaluated performance is indicated as a probability associated with each network space. The method then identifies a subset of the network spaces that has the highest probabilities, and selects a target network space from the subset based on model complexity.
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