7 sonuçlar
Arama Sonuçları
Listeleniyor 1 - 7 / 7
Yayın Network synchronization: Spectral versus statistical properties(Elsevier B.V., 2006-12) Atay, Fatihcan Mehmet; Bıyıkoğlu, Türker; Jost, JürgenWe consider synchronization of weighted networks, possibly with asymmetrical connections. Focusing on causal relations rather than the observed correlations, we show that the synchronizability of networks cannot be directly inferred from their statistical properties. Small local changes in the network structure can sensitively affect the eigenvalues relevant for synchronization, while the gross statistical network properties remain essentially unchanged. Consequently, commonly used statistical properties, including the degree distribution, degree homogeneity, average degree, average distance, degree correlation and clustering coefficient, can fail to characterize the synchronizability of networks in terms of causal relations, despite the observed correlations.Yayın Signals of chaotic behavior in PMMA(Pergamon-Elsevier Science, 2003-07) Hacınlıyan, Avadis Simon; Skarlatos, Yani; Şahin, Gökhan; Akın, Güzin GülsünThe time evolution of the current passing through PMMA polymer thin films under 10 V at 23degreesC (296 K) was sampled at intervals ranging from 1 to 20 s. The data showed chaotic behavior in the context of pinned charge density waves [Phys. Rev. B 41 (1990) 11522]. The resultant time series has been analyzed by means of TISEAN, time series analysis software [The TISEAN package CHAOS 9 (1999) 413]. The analysis has revealed a positive maximal Lyapunov exponent. This is also corroborated by a calculation of the fractal dimension and application of the Kaplan-Yorke conjecture. In the analysis two widely separated time scales have been observed; the first zero crossing of the correlation function at 8380 s and the first marked minimum of the average mutual information at 40 s.Yayın Spectral correlation of a digital pulse stream modulated by a cyclostationary sequence in the presence of timing jitter(IEEE-INST Electrical Electronics Engineers Inc, 2009-02) Öner, Mustafa MengüçCyclostationarity is an inherent characteristic of many communication signals, which can be exploited for performing various signal processing tasks. Imperfections in the signal generation that affect the cyclic statistics of a signal may lead to a degradation in the performance of signal processing algorithms which make use of this cyclostationary behaviour. One typical source of imperfection encountered in digital signalling techniques is random jitter in the pulse timing. In this work, we systematically derive analytical expressions for the cyclic statistics of digital baseband signalling schemes in the presence of timing jitter, under the assumption that the generating wide sense cyclostationary data sequence and the stationary jitter process are statistically independent.Yayın On the spectral correlation of UWB impulse radio signals(IEEE-INST Electrical Electronics Engineers Inc, 2008-10) Öner, Mustafa MengüçCyclostationarity is an inherent characteristic of many communication signals, which can be exploited for performing various signal processing tasks. Determining the cyclic statistics of a signal of interest is often necessary in the design of signal processing systems exploiting this cyclostationary behaviour. This work investigates the second order cyclic statistics of various signalling schemes employed in ultra wideband impulse radio systems. Analytical expressions are derived for the cyclic autocorrelation and spectral correlation density functions.Yayın A novel representation method for electromyogram (EMG) signal with predefined signature and envelope functional bank(IEEE, 2004) Gürkan, Hakan; Güz, Ümit; Yarman, Bekir Sıddık BinboğaIn this paper, a new method to model EMG signals by means of "Predefined Signature and Envelope Functional Banks (PSEB)" is presented. Since EMG signals present quasi-stationary behavior, any EMG signal Xi is modeled by the form of Xi ? Ci?K?R on a frame bases in this work. In this model, ?R is defined as the Predefined Signature Vector (PSV); ?K is referred to as Predefined Envelope Vector (PEV) and Ci is called the Frame-Scaling Coefficient (FSC). EMG signal for each frame is described in terms of the two indices "R" and "K" of PSEB and the frame -scaling coefficient Ci. Furthermore, It has been shown that the new method of modeling provides significant data compression while preserving the clinical information in the reconstructed signal.Yayın Cyclostationarity based blind block timing estimation for alamouti coded MIMO signals(IEEE, 2017-06) Gül, Serhat; Öner, Mustafa Mengüç; Çırpan, Hakan AliBlind parameter estimation algorithms provide a powerful tool for application scenarios where the use of training or pilot sequences is not desirable, e.g., in order to improve the bandwidth efficiency of the transmission, or in noncooperative scenarios where such sequences are not available to the receiver. This letter proposes a blind block timing estimation algorithm for Alamouti space-time block coded signals exploiting the second order joint cyclostationary characteristics of the received signal vector, which is induced by the space time block coding operation performed by the transmitter. The proposed algorithm outperforms the existing algorithms by a wide margin.Yayın TurkEmbed: Turkish embedding model on natural language inference & sentence text similarity tasks(Institute of Electrical and Electronics Engineers Inc., 2025) Ezerceli, Özay; Gümüşçekiçci, Gizem; Erkoç, Tuğba; Özenç, BerkeThis paper introduces TurkEmbed, a novel Turkish language embedding model designed to outperform existing models, particularly in Natural Language Inference (NLI) and Semantic Textual Similarity (STS) tasks. Current Turkish embedding models often rely on machine-translated datasets, potentially limiting their accuracy and semantic understanding. TurkEmbed utilizes a combination of diverse datasets and advanced training techniques, including matryoshka representation learning, to achieve more robust and accurate embeddings. This approach enables the model to adapt to various resource-constrained environments, offering faster encoding capabilities. Our evaluation on the Turkish STS-b-TR dataset, using Pearson and Spearman correlation metrics, demonstrates significant improvements in semantic similarity tasks. Furthermore, TurkEmbed surpasses the current state-of-the-art model, Emrecan, on All-NLI-TR and STS-b-TR benchmarks, achieving a 1-4% improvement. TurkEmbed promises to enhance the Turkish NLP ecosystem by providing a more nuanced understanding of language and facilitating advancements in downstream applications.
