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This paper deals with model comparison based on the Jeffrey's divergence (JD). More particularly, after providing the JD between the joint distributions of k consecutive values of a white noise and the ones of a real moving-average or autoregressive model, the JD between real 1st-order MA and real 1st-order AR models is studied. Except when the 1st MA parameter is equal to 1, we show that, after a...
Most successful deep learning algorithms for action recognition extend models designed for image-based tasks such as object recognition to video. Such extensions are typically trained for actions on single video frames or very short clips, and then their predictions from sliding-windows over the video sequence are pooled for recognizing the action at the sequence level. Usually this pooling step uses...
The stream cipher ChaCha20 and the MAC function Poly1305 have been published as IETF RFC 7539. Since then, the industry is starting to use it more often. For example, it has been implemented by Google in their Chrome browser for TLS and also support has been added to OpenSSL, as well as OpenSSH. It is often claimed, that the algorithms are designed to be resistant to side-channel attacks. However,...
Neural associative memory (AM) is one of the critical building blocks for cognitive workloads such as classification and recognition. It learns and retrieves memories as humans brain does, i.e., changing the strengths of plastic synapses (weights) based on inputs and retrieving information by information itself. One of the key challenges in designing AM is to extend memory capacity (i.e., memories...
There are several analysis models and corresponding temporal analysis techniques for checking whether applications executed on multiprocessor systems meet their real-time constraints. However, currently there does not exist an exact end-to-end latency analysis technique for Homogeneous Synchronous Dataflow with auto-concurrency (HSDFa) models that takes the correlation between the firing durations...
Stochastic circuits (SCs) offer tremendous areaand power-consumption benefits at the expense of computational inaccuracies. Managing accuracy is a central problem in SC design and has no counterpart in conventional circuit synthesis. It raises a basic question: how to build a systematic design flow for stochastic circuits? We present, for the first time, a systematic design approach to control the...
In this paper, the effect of amplitude and phase errors as well as amplifiers and phase shifters failures on a phased array performance is investigated. It is found that random phase errors and phase shifters failures are dominant factors, they influence the peak sidelobe level, pointing angle accuracy, directive power and the half power beamwidth.
Emergence of big data is directly proportional to the data shared in social media. Audio, video, text or the combination of all the above are the data shared in social media. Social networking is achieved by Social Networking Sites (SNS). In real world business, analysts use software tools to analyze product sales, promotion of brand and also tend to identify influential factors that impact their...
Analog circuits lack perfect accuracy; noise, PVT-Variations, non-linearities, crosstalk and many other effects cause unforeseen deviations that we also call “uncertainties”. In the paper we classify various causes of uncertainties and describe a simple, generic, mathematical model of uncertain signals and systems that is applicable from circuit level up to system level. We show in particular how...
Single electron circuits are proposed for use as a coherent signal source. This paper uses the Monte-Carlo method to investigate the degree of correlation between successive events in long arrays of tunnel junctions. Simulations use ensemble studies starting from a known condition used to compute the probability density functions for time between events. It is shown that longer arrays produce more...
Vehicle safety airbags can protect occupants from vehicle collisions, but there are still some shortcomings, thus need to be constantly improved. In occupant restraint system simulation, the establishment of a reasonable airbag model determines whether the simulation results are consistent with the actual test results. The aim of this study is to establish a precise airbag model for vehicle occupant...
A data-driven model predictive control (MPC) in modified partial least squares (PLS) framework is proposed in this paper after a brief summary of MPC strategy in PLS framework. A theoretical comparison between data-driven MPC strategy in these two framework is presented, which demonstrates that MPC in modified PLS framework benefits in both computation complexity and robustness. The feature of modeling...
In order to obtain more accurate results, an adaptive Kalman filter is proposed to track Global Navigation Satellite System (GNSS) signal carrier in the presence of high dynamic. After reviewing the classical adaptive methods, an improved adaptive method is discussed theoretically. The improved adaptive Kalman filter is well set in terms of the GNSS signal model. Simulation results indicate that the...
In this paper, we propose a cyclostationary noise model for multi-input multi-output (MIMO) narrowband power line communication (NB-PLC) based on frequency-shift (FRESH) filtering. The MIMO FRESH filters are designed to shape a multi-input white noise spectrum to a muti-output cyclic spectrum extracted from experimental noise measurements of three-phase low-voltage power lines. The noise modeling...
Prices of derivative contracts, such as options, traded in the financial markets are expected to have complex relationships to fluctuations in the values of the underlying assets, the time to maturity and type of exercise of the contracts as well as other macroeconomic variables. Hutchinson, Lo and Poggio showed in 1994 that a non-parametric artificial neural network may be trained to approximate...
The inherent intangible nature, complexity, context-specific interpretations of emotions make it difficult to quantify and model affective space. Dimensional theory is one of the effective methods to describe and model emotions. Despite recent advances in affective computing, modeling continuous affective space remains a challenge. Here, we present a computational framework to study the role of functional...
We introduce a novel dynamic model for discrete time-series data, in which the temporal sampling may be nonuniform. The model is specified by constructing a hierarchy of Poisson factor analysis blocks, one for the transitions between latent states and the other for the emissions between latent states and observations. Latent variables are binary and linked to Poisson factor analysis via Bernoulli-Poisson...
Discovering and modeling lead-lag relations is a critical task in a variety of domains, including energy management, financial markets and environment monitoring. This task becomes more challenging when processing massive and highly dynamic data sources, often produced by sensors and live feeds that collect data about evolving entities in the real world. To cope with this data volume and velocity,...
SQL injection is the most common web application vulnerability. The vulnerability can be generated unintentionally by software developer during the development phase. To ensure that all secure coding practices are adopted to prevent the vulnerability. The framework of SQL injection prevention using compiler platform and machine learning is proposed. The machine learning part will be described primarily...
In this paper, we propose algorithms for biomolecular docking sites selection problem by various machine learning approaches with selective features reduction. The proposed method can reduce the number of various amino acid features before constructing machine learning prediction models. Given frame boxes with features, the proposed method analyzes the important features by correlation coefficients...
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