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5 articles for “euclidean norm”
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Some characterizations of Euclidean Norms Among Minkowski Norms
Abstract: In this paper we study the geometry of indicatrix of Minkowski norms. We give in dimension three, two geometric characterizations of Euclidean norms among Minkowski norms.Cite this ArticleReza Chavosh Khatamy, Dariush Latifi, Parisa Bahmandoust, Some character-izations of Euclidean norms among Minkowski norms. Research & Reviews: Discrete Mathematical Structures. 2015; 2(1): 15–19p.
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 2, Issue 1, 2015 · pp. 15–19 Read article
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An Improved K-means Clustering Algorithm for Classification of Odor/Gas Sensor Data Using Normalized Cosine Distance Parameter
Abstract: This paper presents a novel approach of K-means Clustering for classification of odors/gases (E-nose) using cosine distance as a distance parameter. A sensor array constituting five sensors is exposed to four different types of gases to extract data. The problem of classifying the data into respective classes in considered as a K-means Clustering task. To quantify the amount of similitude between the data corresponding to same classes; usually euclidean distance …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 2, 2015 · pp. 56–60 Read article
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Identification of Thyroid Disease Severity using Fuzzy C-Means
Abstract: Clustering is a primary data description method in data mining which group’s most similar data. Data clustering is one of the important problems in the fields of data mining, bio-informatics and pattern recognition. Various algorithms are used to solve this problem. This paper presents the performance analysis of k-means clustering algorithm and compares it with fuzzy C- Means (FCM) algorithm on Thyroid disease data set. We also find the accuracy …
Published in Journal of Advanced Database Management & Systems · Vol. 1, Issue 1, 2014 · pp. 13–19 Read article
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Automatic Language Identification using Basic Signal Class
Abstract: Automatic language identification (ASLID) is a problem of identifying an unknown language from spoken utterance by a computer. A segmental approach to ASLID based on the assumption that the acoustic structure of languages can be estimated by segmenting speech into three basic classes of speech signals. This paper presents a procedure of ASLID with the details of methodology and the results without recognizing the words, but the lengths segments of …
Published in Trends in Electrical Engineering · Vol. 9, Issue 2, 2019 · pp. 12–19 Read article
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Fractional Riemannian Fuzzy C-Means with Time-Series Regularization for Economic Manifold Forecasting
Abstract: A fractional Riemannian fuzzy c-means framework is proposed for uncertain economic forecasting on non-Euclidean data domains. Observations are represented on a Riemannian manifold, cluster centres are intrinsic prototypes, and a latent fuzzy regime signal is regularised by both autoregressive and fractional-memory penalties. The resulting objective couples geometric clustering with time-series consistency, thereby discouraging partitions that are locally plausible but temporally incoherent. Closed-form membership updates, exponential-map centre updates, normal equations for …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 49–55 Read article