A CMOS operational amplifier with input/output rail-to-rail range is presented. The circuit operates with a 1-V single supply. It uses dynamically biased input level shifters, controlled by a novel tuning scheme, to extend the input common-mode voltage range from one rail to the other. The tuning circuit takes the total biasing current of the amplifier input stage and, hence, its small-signal r...

Most non-trivial applications use input/output (I/O), such as network communication. When model checking such an application, a simple state space exploration scheme is not applicable, as the process being model checked would replay I/O operations when revisiting a given state. Thus a software model checker requires a faithful model, or it has to encapsulate such operations in a cache layer tha...

The paper studies testing based on input/output transition systems, also known as input/output automata. It is assumed that a tester can never prevent an implementation under test (IUT) from producing outputs, while the IUT does not block inputs from the tester, either. Thus, input from the tester and output from the IUT may occur simultaneously and should be queued in finite buffers between th...

Recurrent neural language models are the state-of-the-art models for language modeling. When the vocabulary size is large, the space taken to store the model parameters becomes the bottleneck for the use of recurrent neural language models. In this paper, we introduce a simple space compression method that randomly shares the structured parameters at both the input and output embedding layers o...

Inspired by recent research, we explore ways to model the highly morphological Finnish language at the level of characters while maintaining the performance of word-level models. We propose a new Character-to-Word-to-Character (C2W2C) compositional language model that uses characters as input and output while still internally processing word level embeddings. Our preliminary experiments, using ...

We look at the problem of estimation for partially observed risk sensitive control problems with nite state input and output sets and receding horizon We describe architectures for risk sensitive controllers and estimation and we state conditions under which both the estimated model converges to the true model and the control policy will converge to the optimal risk sensitive policy

abstract aims: one of the consequences of taking ground water into surface is changing its chemical quality, specially increasing the concentration of dissolved salts. this research was performed in order to analyze growth possibility of heterotrophic bacteria in the membrane of active desalination plants in kashan city, iran. instrument & methods: this descriptive cross-sectional study was don...

We present an analysis of the work of human participants in addressing design problems by analogy. We describe a computer program, called Galatea, that simulates the visual input and output of four experimental participants. Since Galatea is an operational computer program, it makes specific commitments about the visual representations and reasoning it uses for analogical transfer. In particula...

This paper studies the problem of diffusion in Markovian models, such as hidden Markov models (HMMs) and how it makes very difficult the task of learning of long-term dependencies in sequences. Using results from Markov chain theory, we show that the problem of diffusion is reduced if the transition probabilities approach 0 or 1. Under this condition, standard HMMs have very limited modeling ca...

Here it is shown that the use of weighted l2-norms is a useful tool for the analysis of adaptive control loops based on non-linear models. We apply a simpliied feedback linearizing controller based on a linearly parameterized non-linear discrete-time input/output model with slowly time-varying parameters. The main assumption that is required in order to apply weighted l2-norms for analysis is t...