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eess.SP2026
Inverse Design of Compact and Wideband Inverted Doherty Power Amplifiers Using Deep Learning
Han Zhou, Haojie Chang, David Widen +1
This paper presents a deep learning-assisted methodology for the inverse synthesis of a compact, wideband inverted Doherty power amplifier (PA). Convolutional neural networks (CNNs…
eess.SP2026
Deep-Learning-Based Pixelated Microwave Filter Design and Characterization using Electro-Optical Electric-Field Measurements
Han Zhou, Richard Bannister, Caspar Pierce +9
Traditional microwave filter design typically relies on iterative parameter tuning and predefined topologies, which limits design space and increases development time. This study u…
eess.SP2026
Deep Learning-Driven Inverse Design of Doherty Power Amplifiers Using Pixelated Combiners and Dual-State Impedance Synthesis
Han Zhou, Haojie Chang, David Widen +1
The output combiner of a Doherty power amplifier (PA) integrates load modulation, impedance matching, and phase compensation within a single network, making its design and synthesi…