Search results for "97"
showing 10 items of 1081 documents
Modeling Networks of Probabilistic Memristors in SPICE
2021
Efficient simulation of stochastic memristors and their networks requires novel modeling approaches. Utilizing a master equation to find occupation probabilities of network states is a recent major departure from typical memristor modeling [Chaos, solitons fractals 142, 110385 (2021)]. In the present article we show how to implement such master equations in SPICE – a general purpose circuit simulation program. In the case studies we simulate the dynamics of acdriven probabilistic binary and multi-state memristors, and dc-driven networks of probabilistic binary and multi-state memristors. Our SPICE results are in perfect agreement with known analytical solutions. Examples of LTspice code are…
Acoustic Scene Classification with Squeeze-Excitation Residual Networks
2020
Acoustic scene classification (ASC) is a problem related to the field of machine listening whose objective is to classify/tag an audio clip in a predefined label describing a scene location (e. g. park, airport, etc.). Many state-of-the-art solutions to ASC incorporate data augmentation techniques and model ensembles. However, considerable improvements can also be achieved only by modifying the architecture of convolutional neural networks (CNNs). In this work we propose two novel squeeze-excitation blocks to improve the accuracy of a CNN-based ASC framework based on residual learning. The main idea of squeeze-excitation blocks is to learn spatial and channel-wise feature maps independently…
Isotonic regression for metallic microstructure data: estimation and testing under order restrictions
2021
Investigating the main determinants of the mechanical performance of metals is not a simple task. Already known physical inspired qualitative relations between 2D microstructure characteristics and 3D mechanical properties can act as the starting point of the investigation. Isotonic regression allows to take into account ordering relations and leads to more efficient and accurate results when the underlying assumptions actually hold. The main goal in this paper is to test order relations in a model inspired by a materials science application. The statistical estimation procedure is described considering three different scenarios according to the knowledge of the variances: known variance ra…
A New Nonparametric Estimate of the Risk-Neutral Density with Applications to Variance Swaps
2021
We develop a new nonparametric approach for estimating the risk-neutral density of asset prices and reformulate its estimation into a double-constrained optimization problem. We evaluate our approach using the S\&P 500 market option prices from 1996 to 2015. A comprehensive cross-validation study shows that our approach outperforms the existing nonparametric quartic B-spline and cubic spline methods, as well as the parametric method based on the Normal Inverse Gaussian distribution. As an application, we use the proposed density estimator to price long-term variance swaps, and the model-implied prices match reasonably well with those of the variance future downloaded from the CBOE websi…
Quantum Phases and Spin Liquid Properties of 1T-TaS2
2021
Quantum materials exhibiting magnetic frustration are connected to diverse phenomena including high-Tc superconductivity, topological order and quantum spin liquids (QSLs). A QSL is a quantum phase (QP) related to a quantum-entangled fluid-like state of matter. Previous experiments on QSL candidate materials are usually interpreted in terms of a single QP, although theories indicate that many distinct QPs are closely competing in typical frustrated spin models. Here we report on combined temperature-dependent muon spin relaxation and specific heat measurements for the triangular-lattice QSL candidate material 1T-TaS2 that provide evidence for competing QPs. The measured properties are assig…
Ohmic Contacts on p-Type Al-Implanted 4H-SiC Layers after Different Post-Implantation Annealings
2019
This paper reports on the electrical activation and Ohmic contact properties on p-type Al-implanted silicon carbide (4H-SiC). In particular, the contacts were formed on 4H-SiC-implanted layers, subjected to three different post-implantation annealing processes, at 1675 °
Toward Optimal LSTM Neural Networks for Detecting Algorithmically Generated Domain Names
2021
Malware detection is a problem that has become particularly challenging over the last decade. A common strategy for detecting malware is to scan network traffic for malicious connections between infected devices and their command and control (C&C) servers. However, malware developers are aware of this detection method and begin to incorporate new strategies to go unnoticed. In particular, they generate domain names instead of using static Internet Protocol addresses or regular domain names pointing to their C&C servers. By using a domain generation algorithm, the effectiveness of the blacklisting of domains is reduced, as the large number of domain names that must be blocked g…
"Sipensamos en espacios de perpetración, no hay nada comparable al Valle de los Caídos". Conversación con Francisco Ferrándiz
2021
Optical sectioning microscopy through single-shot Lightfield protocol
2020
Optical sectioning microscopy is usually performed by means of a scanning, multi-shot procedure in combination with non-uniform illumination. In this paper, we change the paradigm and report a method that is based in the light field concept, and that provides optical sectioning for 3D microscopy images after a single-shot capture. To do this we fi rst capture multiple orthographic perspectives of the sample by means of Fourier-domain integral microscopy (FiMic). The second stage of our protocol is the application of a novel refocusing algorithm that is able to produce optical sectioning in real time, and with no resolution worsening, in the case of sparse f luorescent samples.We provide the…