Given a probability distribution D over the non-negative integers, a D-repeat channel acts on an input symbol by repeating it a number of times distributed as D. For example, the binary deletion channel (D = Bernoulli...
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Blockchain testing plays a critical role in the maturation of blockchain technology by ensuring the quality of implemented functional and non-functional requirements. In the new global economy, rapid time to market ha...
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Noninvasive diffuse optical spectroscopy (DOS) is promising as an adjunct diagnostic imaging technique for distinguishing benign and malignant breast lesions. However, most DOS approaches require normalizing lesion op...
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Control barrier functions have been widely used for synthesizing safety-critical controls, often via solving quadratic programs. However, the existence of Gaussian-type noise may lead to unsafe actions and result in s...
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The paper presents the rotated 3D-printed dielectric lens assembly with an ultra-wideband (UWB) antenna for use in the beam-steering applications. The focus is on achieving beam steering by combining the rotated 3D-pr...
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ISBN:
(数字)9798350383591
ISBN:
(纸本)9798350383607
The paper presents the rotated 3D-printed dielectric lens assembly with an ultra-wideband (UWB) antenna for use in the beam-steering applications. The focus is on achieving beam steering by combining the rotated 3D-printed dielectric lens assembly with a hemispherical lens and UWB antenna. The UWB antenna is fabricated on an FR-4 substrate, while the hemispherical lens and the rotated 3D-printed lens assembly are made from Acrylonitrile Butadiene Styrene (ABS). To enable the hemispherical lens to rotate to the specified angle, a set of rotatable 3D-printed lenses was etched to determine five angles: -60degrees, -30degrees, 0degrees, 30degrees, and 60degrees. Both simulation and measurement results indicate that at a beginning frequency of 3.5 GHz, the beam cannot be steered when using the UWB antenna with the 3D-printed ABS lens rotated hemispherical lens assembly. However, at middle and high frequencies of 7.0 GHz and 10.0 GHz, respectively, the beam can be steered according to the direction of rotation of the hemispherical lens.
This study focuses on model order reduction for large-scale sparse index-2 descriptor systems that arise from practical problems governed by the semi-discrete Naiver Stokes equation, such as blood flow through the car...
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High-tech improvements with reference for health advance to develop numerous medical tools have been build to support doctors and nurses performances. This analysis research applied web-based system of infusion monito...
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Chaos-based random bit generators are abundantly used in chaos-based encryption and security applications, as a fast, deterministic source of randomness, to perform actions like permutation and substitution. The chaot...
Chaos-based random bit generators are abundantly used in chaos-based encryption and security applications, as a fast, deterministic source of randomness, to perform actions like permutation and substitution. The chaotic map used as a source of randomness though may heavily affect the bit generator’s statistical randomness, key space, and speed. Thus, any given bit generator may not be equally efficient for all the chaotic maps used as a seed. Motivated by this, the present work considers a bit generator that utilizes a common modulo-based hashing technique, and studies its performance under a plethora of different chaotic maps. For each map, the generator is evaluated with respect to randomness, key space, and operations per bit ratio. This analysis can serve as a guideline for random bit generator usage in future chaos-based encryption designs.
In this paper, the voltage regulation of DC-DC boost converters is investigated in the existence of unmodeled system dynamics and load perturbations. An adaptive observer based sliding mode controller (SMC) is propose...
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ISBN:
(数字)9798331516680
ISBN:
(纸本)9798331516697
In this paper, the voltage regulation of DC-DC boost converters is investigated in the existence of unmodeled system dynamics and load perturbations. An adaptive observer based sliding mode controller (SMC) is proposed based on the radial basis function (RBF) neural networks for estimating the uncertain system function. The parameters of the RBF are updated online based on the adaptive law. The adaptive control law is developed based on the Lyapunov synthesis for the RBF model. The Lyapunov theory is utilized for proving the stability of the overall system. The chattering phenomenon is eliminated, and the robust action of the controller is ensured. For checking the effectiveness of the designed robust and adaptive controller, comparative simulations are carried out. Simulation results show better dynamic regulation of the boost converter compared to the conventional control in the presence of uncertainties and unmodeled dynamics.
Many fundamental problems in machine learning can be formulated by the convex program \[ \min_{\theta\in \mathbb{R}^d}\ \sum_{i=1}^{n}f_{i}(\theta), \] where each fi is a convex, Lipschitz function supported on a subs...
ISBN:
(纸本)9781713871088
Many fundamental problems in machine learning can be formulated by the convex program \[ \min_{\theta\in \mathbb{R}^d}\ \sum_{i=1}^{n}f_{i}(\theta), \] where each fi is a convex, Lipschitz function supported on a subset of di coordinates of θ. One common approach to this problem, exemplified by stochastic gradient descent, involves sampling one fi term at every iteration to make progress. This approach crucially relies on a notion of uniformity across the fi's, formally captured by their condition number. In this work, we give an algorithm that minimizes the above convex formulation to e-accuracy in $\widetilde{O}(\sum_{i=1}^n d_i \log (1 /\epsilon))$ gradient computations, with no assumptions on the condition number. The previous best algorithm independent of the condition number is the standard cutting plane method, which requires O(nd log(1/ε)) gradient computations. As a corollary, we improve upon the evaluation oracle complexity for decomposable submodular minimization by [Axiotis, Karczmarz, Mukherjee, Sankowski and Vladu, ICML 2021]. Our main technical contribution is an adaptive procedure to select an fi term at every iteration via a novel combination of cutting-plane and interior-point methods.
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