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2020 – today
- 2024
[j11]Hao-Hsuan Chang
, Ci-Ren Chen, Tai-Cheng Lee:
A 511-μW 89-dB-SNDR Asynchronous SAR-ISDM ADC With Noise Shaping Dynamic Amplifier and Time-Domain Noise-Slicing Technique. IEEE J. Solid State Circuits 59(7): 2199-2208 (2024)- [j10]Vishnu V. Ratnam, Hao Chen, Hao-Hsuan Chang, Abhishek Sehgal, Charlie Zhang:
Optimal Preprocessing of WiFi CSI for Sensing Applications. IEEE Trans. Wirel. Commun. 23(9): 10820-10833 (2024) - [c11]Hao-Hsuan Chang, Vishnu V. Ratnam, Hao Chen, Junsu Choi, Charlie Jianzhong Zhang:
Multi-Person Respiration Rate Estimation With Single Pair Of Transmit And Receive Antenna. ICASSP 2024: 13096-13100 - 2023
- [j9]Hao-Hsuan Chang, Hao Chen, Jianzhong Zhang, Lingjia Liu:
Decentralized Deep Reinforcement Learning Meets Mobility Load Balancing. IEEE/ACM Trans. Netw. 31(2): 473-484 (2023) - [j8]Hao-Hsuan Chang, Yifei Song, Thinh T. Doan, Lingjia Liu:
Federated Multi-Agent Deep Reinforcement Learning (Fed-MADRL) for Dynamic Spectrum Access. IEEE Trans. Wirel. Commun. 22(8): 5337-5348 (2023) - [i5]Vishnu V. Ratnam, Hao Chen, Hao-Hsuan Chang, Abhishek Sehgal, Jianzhong Zhang:
Optimal preprocessing of WiFi CSI for sensing applications. CoRR abs/2307.12126 (2023) - 2022
- [j7]Hao-Hsuan Chang, Lingjia Liu, Jianan Bai, Alex Pidwerbetsky, Allan Berlinsky, Joe Huang, Jonathan D. Ashdown, Kurt A. Turck, Yang Yi:
Resource Allocation for D2D Cellular Networks With QoS Constraints: A DC Programming- Based Approach. IEEE Access 10: 16424-16438 (2022) - [j6]Hao-Hsuan Chang, Tung-Cheng Lin, Tai-Cheng Lee:
A Single-Channel 1-GS/s 7.48-ENOB Parallel Conversion Pipelined SAR ADC With a Varactor-Based Residue Amplifier. IEEE Trans. Circuits Syst. II Express Briefs 69(4): 2021-2025 (2022) - [j5]Hao-Hsuan Chang, Lingjia Liu, Yang Yi:
Deep Echo State Q-Network (DEQN) and Its Application in Dynamic Spectrum Sharing for 5G and Beyond. IEEE Trans. Neural Networks Learn. Syst. 33(3): 929-939 (2022) - [c10]Yifei Song, Hao-Hsuan Chang, Lingjia Liu:
Federated Dynamic Spectrum Access through Multi-Agent Deep Reinforcement Learning. GLOBECOM 2022: 3466-3471 - [c9]Hao-Hsuan Chang, R. B. Sai Sree, Hao Chen, Jianzhong Zhang, Lingjia Liu:
MADRL Based Scheduling for 5G and Beyond. MILCOM 2022: 873-878 - [c8]Yen-Po Lai, Hao-Hsuan Chang, Tai-Cheng Lee:
An Asynchronous Zero-Crossing-Based Incremental Delta-Sigma Converter. VLSI-DAT 2022: 1-4 - 2021
- [b1]Hao-Hsuan Chang:
Deep Reinforcement Learning for Next Generation Wireless Networks with Echo State Networks. Virginia Tech, Blacksburg, VA, USA, 2021 - [i4]Yifei Song, Hao-Hsuan Chang, Zhou Zhou, Shashank Jere, Lingjia Liu:
Federated Dynamic Spectrum Access. CoRR abs/2106.14976 (2021) - 2020
- [j4]Lianjun Li, Lingjia Liu, Jianan Bai, Hao-Hsuan Chang, Hao Chen, Jonathan D. Ashdown, Jianzhong Zhang, Yang Yi:
Accelerating Model-Free Reinforcement Learning With Imperfect Model Knowledge in Dynamic Spectrum Access. IEEE Internet Things J. 7(8): 7517-7528 (2020) - [j3]Zhou Zhou, Lingjia Liu, Hao-Hsuan Chang:
Learning for Detection: MIMO-OFDM Symbol Detection Through Downlink Pilots. IEEE Trans. Wirel. Commun. 19(6): 3712-3726 (2020) - [j2]Lianjun Li, Hao Chen, Hao-Hsuan Chang, Lingjia Liu:
Deep Residual Learning Meets OFDM Channel Estimation. IEEE Wirel. Commun. Lett. 9(5): 615-618 (2020) - [c7]Qiang Fan, Jianan Bai, Hao-Hsuan Chang, Lianjun Li, Shiya Liu, Joe Huang, John Burgess, Allan Berlinsky, Alex Pidwerbetsky, Jonathan D. Ashdown, Kurt A. Turck, Lingjia Liu:
Intelligent DSA-assisted clustered IoT networks: neuromorphic computing meets genetic algorithm. NANOCOM 2020: 24:1-24:6 - [i3]Hao-Hsuan Chang, Lingjia Liu, Yang Yi:
Deep Echo State Q-Network (DEQN) and Its Application in Dynamic Spectrum Sharing for 5G and Beyond. CoRR abs/2010.05449 (2020)
2010 – 2019
- 2019
- [j1]Hao-Hsuan Chang, Hao Song, Yang Yi, Jianzhong Zhang, Haibo He, Lingjia Liu:
Distributive Dynamic Spectrum Access Through Deep Reinforcement Learning: A Reservoir Computing-Based Approach. IEEE Internet Things J. 6(2): 1938-1948 (2019) - [c6]Junchao Ma, Hao-Hsuan Chang, Pingzhi Fan, Lingjia Liu:
Machine learning enabled distributed mobile edge computing network. SEC 2019: 350-351 - [c5]Hao-Hsuan Chang, Lingjia Liu, Hao Song, Alex Pidwerbetsky, Allan Berlinsky, Jonathan D. Ashdown, Kurt A. Turck, Yang Yi:
Maximizing System Throughput in D2D Networks Using Alternative DC Programming. GLOBECOM 2019: 1-6 - [c4]Hao Song, Lingjia Liu, Hao-Hsuan Chang, Jonathan D. Ashdown, Yang Yi:
Deep Q-Network Based Power Allocation Meets Reservoir Computing in Distributed Dynamic Spectrum Access Networks. INFOCOM Workshops 2019: 774-779 - [i2]Zhou Zhou, Lingjia Liu, Hao-Hsuan Chang:
Learn to Demodulate: MIMO-OFDM Symbol Detection through Downlink Pilots. CoRR abs/1907.01516 (2019) - 2018
- [i1]Hao-Hsuan Chang, Hao Song, Yang Yi, Jianzhong Zhang, Haibo He, Lingjia Liu:
Distributive Dynamic Spectrum Access through Deep Reinforcement Learning: A Reservoir Computing Based Approach. CoRR abs/1810.11758 (2018) - 2014
- [c3]Jian-Jiun Ding, Wei-Sheng Lai, Hao-Hsuan Chang, Chir-Weei Chang, Chuan-Chung Chang:
Edge adaptive hybrid norm prior method for blurred image reconstruction. APCCAS 2014: 276-279 - [c2]Ying-Jou Chen, Jian-Jiun Ding, Ching-Wen Hsiao, Hao-Hsuan Chang:
A region adaptive encoding algorithm for simple image compression. APCCAS 2014: 595-598 - [c1]Jian-Jiun Ding, Pin-Xuan Lee, Szu-Wei Fu, Hao-Hsuan Chang, Chen-Wei Huang:
End-point preserved stroke extraction. ICAILP 2014: 318-323
Coauthor Index
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