Search results for "reduction"
showing 10 items of 2058 documents
Time and space efficient quantum algorithms for detecting cycles and testing bipartiteness
2016
We study space and time efficient quantum algorithms for two graph problems -- deciding whether an $n$-vertex graph is a forest, and whether it is bipartite. Via a reduction to the s-t connectivity problem, we describe quantum algorithms for deciding both properties in $\tilde{O}(n^{3/2})$ time and using $O(\log n)$ classical and quantum bits of storage in the adjacency matrix model. We then present quantum algorithms for deciding the two properties in the adjacency array model, which run in time $\tilde{O}(n\sqrt{d_m})$ and also require $O(\log n)$ space, where $d_m$ is the maximum degree of any vertex in the input graph.
Dimensionality Reduction via Regression in Hyperspectral Imagery
2015
This paper introduces a new unsupervised method for dimensionality reduction via regression (DRR). The algorithm belongs to the family of invertible transforms that generalize Principal Component Analysis (PCA) by using curvilinear instead of linear features. DRR identifies the nonlinear features through multivariate regression to ensure the reduction in redundancy between he PCA coefficients, the reduction of the variance of the scores, and the reduction in the reconstruction error. More importantly, unlike other nonlinear dimensionality reduction methods, the invertibility, volume-preservation, and straightforward out-of-sample extension, makes DRR interpretable and easy to apply. The pro…
Low-Power Audio Keyword Spotting using Tsetlin Machines
2021
The emergence of Artificial Intelligence (AI) driven Keyword Spotting (KWS) technologies has revolutionized human to machine interaction. Yet, the challenge of end-to-end energy efficiency, memory footprint and system complexity of current Neural Network (NN) powered AI-KWS pipelines has remained ever present. This paper evaluates KWS utilizing a learning automata powered machine learning algorithm called the Tsetlin Machine (TM). Through significant reduction in parameter requirements and choosing logic over arithmetic based processing, the TM offers new opportunities for low-power KWS while maintaining high learning efficacy. In this paper we explore a TM based keyword spotting (KWS) pipe…
On differences and similarities in the analysis of Lorenz, Chen, and Lu systems
2015
Currently it is being actively discussed the question of the equivalence of various Lorenz-like systems and the possibility of universal consideration of their behavior (Algaba et al., 2013a,b, 2014b,c; Chen, 2013; Chen and Yang, 2013; Leonov, 2013a), in view of the possibility of reduction of such systems to the same form with the help of various transformations. In the present paper the differences and similarities in the analysis of the Lorenz, the Chen and the Lu systems are discussed. It is shown that the Chen and the Lu systems stimulate the development of new methods for the analysis of chaotic systems. Open problems are discussed.
Theoretical and Experimental Studies on the Influence of Process Parameters on Strains and Forces of Single Point Incremental Forming
2014
These paper aims to determine the influence of the most important geometrical parameters (vertical step and punch diameter) on the main strains, thickness reduction and the forces along two directions during the single point incremental forming process (SPIF). The paper comprises a comparative numericalexperimental study, for a simple geometry part obtained by incremental forming. In fact, in the first stage, the punch has a vertical motion with the value of one vertical step. In the second stage, the punch follows a linear trajectory along one side of the die. After each linear trajectory the punch has successive vertical motions, taking one vertical step at a time until the entire geometr…
Design Of Experiments for the optimization the process parameters of thixotropic aluminum alloy
2006
The success of the thixoforming process depends on the possibility to confer to material, when it is found in the semisolid state, a microstructure characterized by globular particles of solid phase surrounded by a continuous film of liquid phase; such microstructure is obtainable through particular thermo-mechanical treatments. In the present research, in order to optimize the influence of process parameters in the step in which the thixotropic properties are conferred to the AA7075 aluminum alloy, the statistic technique of the Design Of Experiments (DOE) has been used. The advantages in the application of such technique are expressible in terms of reduction the times of development of pr…
Physicochemical and technological properties of beef burger as influenced by the addition of pea fibre
2019
This study aimed to evaluate the physicochemical characteristics and sensory attributes of beef burgers with the addition of pea fibre as a partial substitute of meat or fat. Three formulations were prepared: control (CON) – similar to the commercial formulation; fibre/less meat (FLM)—5% meat reduction and addition of 1% pea fibre; fibre/less fat (FLF)—7% fat reduction and addition of 1% pea fibre. Non‐significant differences were obtained for pH, colour parameters (L* and b*), texture profile, cooking loss and size reduction among formulations. Moreover, sensory analysis with consumers of beef burgers did not indicate differences among the formulations for all the analysed attributes. Ther…
Combining feature extraction and expansion to improve classification based similarity learning
2017
Abstract Metric learning has been shown to outperform standard classification based similarity learning in a number of different contexts. In this paper, we show that the performance of classification similarity learning strongly depends on the data format used to learn the model. We then present an Enriched Classification Similarity Learning method that follows a hybrid approach that combines both feature extraction and feature expansion. In particular, we propose a data transformation and the use of a set of standard distances to supplement the information provided by the feature vectors of the training samples. The method is compared to state-of-the-art feature extraction and metric lear…
Fast Distributed Subspace Projection via Graph Filters
2018
A significant number of linear inference problems in wireless sensor networks can be solved by projecting the observed signal onto a given subspace. Decentralized approaches avoid the need for performing such an operation at a central processor, thereby reducing congestion and increasing the robustness and the scalability of the network. Unfortunately, existing decentralized approaches either confine themselves to a reduced family of subspace projection tasks or need an infinite number of iterations to obtain the exact projection. To remedy these limitations, this paper develops a framework for computing a wide class of subspace projections in a decentralized fashion by relying on the notio…
Analysis of Some Innovative and Flexible Sheet Forming Processes
2002
In the field of sheet forming, innovative and flexible processes that do not impose the use of expensive conventional equipments and/or do not require time consuming set-up operations have become, nowadays, a rather promising research topic. Two different main lines are currently followed: the former is based on the development of new stamping processes based on the utilization of flexible media, while the latter is aimed to develop so called progressive forming processes (spinning and incremental forming). Both hydro-forming and incremental forming permit a very relevant reduction of the tooling and set-up costs and improve process flexibility. These items are discussed in detail in the pa…