Successive Approximation Register (SAR) Analog-to-Digital Converters (ADC) seem to become the hottest ADC architecture during the past decade in implementing energy-efficient high performance ADCs. In this overview, we will review what kind of circuit techniques and architectural advances have contributed to place the SAR ADC architecture at its current position, beginning from a single SAR ADC and moving to various hybrid architectures. At the end of this overview, a recently reported compact and high-speed SAR-Flash ADC is introduced as one design example of SAR-based hybrid ADC architecture.

This review paper describes the overall operating principle of a discrete-time delta-sigma modulator (DTDSM) and a continuous-time delta-sigma modulator (CTDSM) using a switched-capacitor (SC). In addition, research that has solved the problems related to each delta-sigma modulator (DSM) is introduced, and the latest developments are explained. This paper describes the chopper-stabilization technique that mitigates flicker noise, which is crucial for the DSM. In the case of DTDSM, this paper addresses the problems that arise when using SC circuits and explains the importance of the operational transconductance amplifier performance of the first integrator of the DSM. In the case of CTDSM, research that has reduced power consumption, and addresses the problems of clock jitter and excess loop delay is described. The recent developments of the analog front end, which have become important due to the increasing use of wireless sensors, is also described. In addition, this paper presents the advantages and disadvantages of the three-opamp instrumentation amplifier (IA), current feedback IA (CFIA), resistive feedback IA, and capacitively coupled IA (CCIA) methods for implementing instrumentation amplifiers in AFEs.

Along with the needs for feasibility in the field of space applications, interests in radiation-hardened electronics is growing rapidly. Gallium nitride (GaN)-based devices have been widely researched so far owing to superb radiation resistance. Among them, research on the most abundant protons in low earth orbit (LEO) is essential. In this paper, proton irradiation effects on parameter changes, degradation mechanism, and correlation with reliability of GaN-based devices are summarized.

As the interest of deep learning, techniques to control the color of images in image processing field are evolving together. However, there is no clear standard for color, and it is not easy to find a way to represent only the color itself like the color-palette. In this paper, we propose a novel color palette extraction system by chroma fine-tuning with reinforcement learning. It helps to recognize the color combination to represent an input image. First, we use RGBY images to create feature maps by transferring the backbone network with well-trained model-weight which is verified at super resolution convolutional neural networks. Second, feature maps are trained to 3 fully connected layers for the color-palette generation with a generative adversarial network (GAN). Third, we use the reinforcement learning method which only changes chroma information of the GAN-output by slightly moving each Y component of YCbCr color gamut of pixel values up and down. The proposed method outperforms existing color palette extraction methods as given the accuracy of 0.9140.