Search results for "Signal processing"
showing 10 items of 2451 documents
Acoustic detection of neutrinos in bedrock
2019
We propose to utilize bedrock as a medium for acoustic detection of particle showers following interactions of ultra-high energy neutrinos. With the density of rock three-times larger and the speed of sound four-times larger compared to water, the amplitude of the generated bipolar pressure pulse in rock should be larger by an order of magnitude. Our preliminary simulations confirm that prediction. Higher density of rock also guarantees higher interaction rate for neutrinos. A noticeably longer attenuation length in rock reduces signal dissipation. The Pyh\"asalmi mine has a unique infrastructure and rock conditions to test this idea and, if successful, extend it to a full-size experiment.
A Simulation Analysis for Assessing the Reliability of AC/DC Hybrid Microgrids - Part II: Port Area and Residential Area
2021
This paper reports the second part of a simulation study with the aim of evaluating the ability of two portions of a hybrid AC/DC MV/LV network in maintaining their operation in off-grid mode during the loss of the main AC grid due to a failure. In particular, this paper follows a dual purpose: first, it analysis two microgrids in a residential area and a port zone capability of operating in islanded mode, applying a probabilistic approach, while there is different energy use cases, and second is to evaluate some reliability indicators.
Directionlets: Anisotropic Multidirectional representation with separable filtering
2006
In spite of the success of the standard wavelet transform (WT) in image processing in recent years, the efficiency of its representation is limited by the spatial isotropy of its basis functions built in the horizontal and vertical directions. One-dimensional (1-D) discontinuities in images (edges and contours) that are very important elements in visual perception, intersect too many wavelet basis functions and lead to a nonsparse representation. To efficiently capture these anisotropic geometrical structures characterized by many more than the horizontal and vertical directions, a more complex multidirectional (M-DIR) and anisotropic transform is required. We present a new lattice-based pe…
Comparison Between Conventional and Vegetated Roof by Means of a Dynamic Simulation
2015
In this paper, a dynamic simulation of a building located in the Campus University of Palermo, Italy, has been carried out. We considered two different scenarios; in the first one, the building as it is, with a conventional covering, while in the second one the roof was equipped with a green roof. The results of the two simulations have been compared, suggesting that such building component could contribute to the energy savings of the building. However, it has to be considered as part of other possible actions devoted to improve the energy efficiency of the whole building. (C) 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC-BY-NC-ND license (http://…
Requirements for Energy Efficient Edge Computing: A Survey
2018
Internet of Things is evolving heavily in these times. One of the major obstacle is energy consumption in the IoT devices (sensor nodes and wireless gateways). The IoT devices are often battery powered wireless devices and thus reducing the energy consumption in these devices is essential to lengthen the lifetime of the device without battery change. It is possible to lengthen battery lifetime by efficient but lightweight sensor data analysis in close proximity of the sensor. Performing part of the sensor data analysis in the end device can reduce the amount of data needed to transmit wirelessly. Transmitting data wirelessly is very energy consuming task. At the same time, the privacy and s…
Optimization of Linearized Belief Propagation for Distributed Detection
2020
In this paper, we investigate distributed inference schemes, over binary-valued Markov random fields, which are realized by the belief propagation (BP) algorithm. We first show that a decision variable obtained by the BP algorithm in a network of distributed agents can be approximated by a linear fusion of all the local log-likelihood ratios. The proposed approach clarifies how the BP algorithm works, simplifies the statistical analysis of its behavior, and enables us to develop a performance optimization framework for the BP-based distributed inference systems. Next, we propose a blind learning-adaptation scheme to optimize the system performance when there is no information available a pr…
Modeling and Mitigating Errors in Belief Propagation for Distributed Detection
2021
We study the behavior of the belief-propagation (BP) algorithm affected by erroneous data exchange in a wireless sensor network (WSN). The WSN conducts a distributed multidimensional hypothesis test over binary random variables. The joint statistical behavior of the sensor observations is modeled by a Markov random field whose parameters are used to build the BP messages exchanged between the sensing nodes. Through linearization of the BP message-update rule, we analyze the behavior of the resulting erroneous decision variables and derive closed-form relationships that describe the impact of stochastic errors on the performance of the BP algorithm. We then develop a decentralized distribute…
Fuzzy sliding mode control design for a class of disturbed systems
2014
This paper discusses the problem of the fuzzy sliding mode control for a class of disturbed systems. First, a fuzzy auxiliary controller is constructed based on a feedback signal not only to estimate the unknown control term, but also participates in the sliding mode control due to the fuzzy rule employed. Then, we extend our theory into the cases, where some kind of system information can not be obtained, for better use of our theoretical results in real engineering. Finally, some typical numerical examples are included to demonstrate the effectiveness and advantage of the designed sliding mode controller. Refereed/Peer-reviewed
Space-Frequency Quantization for Image Compression With Directionlets
2007
The standard separable 2-D wavelet transform (WT) has recently achieved a great success in image processing because it provides a sparse representation of smooth images. However, it fails to efficiently capture 1-D discontinuities, like edges or contours. These features, being elongated and characterized by geometrical regularity along different directions, intersect and generate many large magnitude wavelet coefficients. Since contours are very important elements in the visual perception of images, to provide a good visual quality of compressed images, it is fundamental to preserve good reconstruction of these directional features. In our previous work, we proposed a construction of critic…
Classification of healthy, Alzheimer and Parkinson populations with a multi-branch neural network
2022
Signal processing, for delimitation of the target events and parametrization, is usually required when instrumented assessment is conducted to determine an individual’s functional status. However, these procedures may rule out relevant information obtained by sensors. To prevent this, the use of models based on neural networks that automatically extract relevant features from the raw signal may improve the characterization of the functional status. Thus, the aim of the study was to determine the classification accuracy of a multi-head convolutional layered neural network (CNN) using a simple functional mobility test in people with different conditions. The raw data from an inertial sensor e…