Inverter-based Operational Transconductance Amplifiers (OTAs) are versatile and friendly scalable analog circuit blocks. Especially for the new CMOS technological nodes, several recent applications have been extensively using them, ranging from Analog Front End (AFE) to analog-to-digital converters (ADC). This work tracks down current advances in inverter-based OTAs design, comparing their basi...

Hybrid analog/digital precoding in millimeter-wave (mmWave) multi-input multi-ouput (MIMO) systems is capable of achieving the near-optimal full-digital performance at reduced hardware cost and power consumption compared to its full-RF digital counterpart. However, having numerous phase shifters still costly, especially when are high resolution. In this paper, we propose a novel twin-resolution...

The purpose of this article is to serve as a light-weight introduction into the mysteries of analog and hybrid computing models from a dynamical systems and programming languages perspective. Hybrid systems are the dynamical systems that combine both models of computation, i.e., have interacting discrete and continuous dynamics. They have found widespread application as models for embedded comp...

Cascadable, CMOS synapse chips containing a cross-bar array of 32x32 (1024) programmable synapses have been fabricated as "building blocks" for fully parallel implementation of neural networks. The synapses are based on a hybrid digital-analog design which utilizes on-Chip 7-bit data latches to store quantized weights and two-quadrant multiplying DAC's to compute weighted outputs. The synapses ...

This paper investigates a hybrid evolutionary-based design system for automated sizing of analog integrated circuits (ICs). A new algorithm, called competitive co-evolutionary differential evolution (CODE), is proposed to design analog ICs with practical user-defined specifications. On the basis of the combination of HSPICE and MATLAB, the system links circuit performances, evaluated through el...

Recently there has been increased research interest in the study of the hybrid dynamical systems (Sun & Ge, 2005) and (Li et al., 2005). These systems involve the interaction of discrete and continuous dynamics. Continuous variables take the values from the set of real numbers and the discrete variables take the values from finite set of symbols. The hybrid systems have the behaviour of an anal...

We present an overview of recently developed data-driven tools for safety analysis of autonomous vehicles and advanced driver assist systems. The core algorithms combine model-based, hybrid system reachability analysis with sensitivity analysis of components with unknown or inaccessible models. We illustrate the applicability of this approach with a new case study of emergency braking systems i...

Recently there has been a shift in material sciences towards the use of non contacting laser optical methods to characterize material behaviour. This development has been driven by the need to test specimens at relatively high temperatures. We present a hybrid system for tracking laser speckles consisting of a Fourier-optical preprocessor followed by a digital signal processing unit that is abl...

Neural-based branch predictors have been among the most accurate in the literature. The recently proposed scaled neural analog predictor, or SNAP, builds on piecewise-linear branch prediction and relies on a mixed analog/digital implementation to mitigate latency as well as power requirements over previous neural predictors. I present an optimized version of the SNAP predictor, hybridized with ...

Mammalian axons are thought to act as digital signaling devices, conveying information only by the timing and rate of all-or-none action potentials. Two recent studies now show that synaptic potentials can also spread far down the axon and influence action potential-triggered transmitter release in a graded, 'analog' manner. Axons thus encode information both about subthreshold and suprathresho...