Multiplexing high‐side load switch using adaptive well biasing

Learning adaptive leg cycles using fitness biasing

This paper discusses the use of fitness biasing to alter the control of a seven microprocessor robot as it shifts from one environment to another. The robot was initially using a gait evolved to work on a smooth surface (tile). When tested on a rough surface (carpet) the learned gait was found to be inappropriate because the legs were causing drag as they repositioned. An efficient move to repo...

Adaptive Hexapod Gait Control Using Anytime Learning with Fitness Biasing

Adaptive learning systems that generate control programs for robots with varying capabilities is of importance in the implementation of autonomous robots. Learning done continuously with the best possible control program running the robot (anytime learning) can achieve the adaptability desired when implemented using some form of evolutionary computation. The difficulty with this method is that ...

A Linear MOS Transconductor Using Source Degeneration and Adaptive Biasing

This paper presents a new configuration for linear MOS voltage-to-current conversion (transconductance). The proposed circuit combines two previously reported linearization methods [1], [2]. The topology achieves 60-dB linearity for a fully balanced input dynamic range up to 1 at a 3.3-V supply voltage, with slightly decreasing performance in the unbalanced case. The linearity is preserved duri...

On-chip mode-division multiplexing switch

BRIAN STERN, XIAOLIANG ZHU, CHRISTINE P. CHEN, LAWRENCE D. TZUANG, JAIME CARDENAS, KEREN BERGMAN, AND MICHAL LIPSON* School of Electrical and Computer Engineering, Cornell University, Ithaca, New York 14853, USA Department of Electrical Engineering, Columbia University, New York, New York 10027, USA Kavli Institute at Cornell for Nanoscale Science, Cornell University, Ithaca, New York 14853, US...

Reduction of Photodiode Nonlinearities by Adaptive Biasing