• Title/Summary/Keyword: difference sequence

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On Some Lacunary Generalized Difference Sequence Spaces of Invariant Means De ned by a Sequence of Modulus Function

  • Atici, Gulcan;Bektas, Cigdem Asma
    • Kyungpook Mathematical Journal
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    • v.51 no.4
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    • pp.385-393
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    • 2011
  • The aim of this paper is to introduce and study the sequence spaces [w, ${\theta}$, F, p, q]$_{\infty}({\Delta}_{\upsilon}^m)$, [w, ${\theta}$, F, p, q]$_1({\Delta}_{\upsilon}^m)$ and [w, ${\theta}$, F, p, q]$_0({\Delta}_{\upsilon}^m)$, which arise from the notions of generalized difference sequence space, lacunary convergence, invariant mean and a sequence of Moduli $F=(f_k)$. We establish some inclusion relations between these spaces under some conditions.

Changes in EEG According to Attention and Concentration Training Programs with Performed Difference Tasks (주의·집중훈련 프로그램의 두 가지 과제수행에 따른 뇌파 변화)

  • Chae, Jung-Byung
    • PNF and Movement
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    • v.12 no.2
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    • pp.97-106
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    • 2014
  • Purpose: The purpose of this study was to investigate changes in EEG through attention. Concentration training and performing tasks are important factors in the improvement of motor learning ability. Methods: In the experiment, 22 healthy people were divided into two groups: the trail making test (TMT) group and the computerized neurocognitive function test (CNT) group. A one-way Neuro Harmony M test to see whether there was a significant difference among the groups. Results: The TMT group showed a significant increase in ${\alpha}$ wave, ${\alpha}$ wave sequence, and ${\beta}$ wave sequence; however, there were no significant differences in SMR wave, SMR wave sequence, and ${\beta}$ wave. The CNT group showed increases in ${\alpha}$ wave, ${\alpha}$ wave sequence, SMR wave, SMR wave sequence, and ${\beta}$ wave sequence; however, there was no significant difference in ${\beta}$ wave. In EEGs before and after two performance tasks were changed, there were significant differences in ${\beta}$ wave, SMR wave, SMR wave sequence; however, there were no significant differences in ${\alpha}$ wave sequence, ${\beta}$ wave, and ${\beta}$ wave sequence. Conclusion: Attention training and concentration training offer feedback and repetition for constant stimulus and response. Moreover, attention training and concentration training can contribute to new studies and motivation by developing fast sensory and motor skills through acceptable visual and auditory stimulation.

SOME SEQUENCE SPACES OVER n-NORMED SPACES DEFINED BY FRACTIONAL DIFFERENCE OPERATOR AND MUSIELAK-ORLICZ FUNCTION

  • Mursaleen, M.;Sharma, Sunil K.;Qamaruddin, Qamaruddin
    • Korean Journal of Mathematics
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    • v.29 no.2
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    • pp.211-225
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    • 2021
  • In the present paper we introduce some sequence spaces over n-normed spaces defined by fractional difference operator and Musielak-Orlicz function 𝓜 = (𝕱i). We also study some topological properties and prove some inclusion relations between these spaces.

Some Paranormed Difference Sequence Spaces Derived by Using Generalized Means

  • MANNA, ATANU;MAJI, AMIT;SRIVASTAVA, PARMESHWARY DAYAL
    • Kyungpook Mathematical Journal
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    • v.55 no.4
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    • pp.909-931
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    • 2015
  • This paper presents some new paranormed sequence spaces $X(r,s,t,p;{\Delta})$ where $X{\in}\{l_{\infty}(p),c(p),c_0(p),l(p)\}$ defined by using generalized means and difference operator. It is shown that these are complete linear metric spaces under suitable paranorms. Furthermore, the ${\alpha}$-, ${\beta}$-, ${\gamma}$-duals of these sequence spaces are computed and also obtained necessary and sufficient conditions for some matrix transformations from $X(r,s,t,p;{\Delta})$ to X. Finally, it is proved that the sequence space $l(r,s,t,p;{\Delta})$ is rotund when $p_n$ > 1 for all n and has the Kadec-Klee property.

An Adaptive Data Compression Algorithm for Video Data (사진데이타를 위한 한 Adaptive Data Compression 방법)

  • 김재균
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.12 no.2
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    • pp.1-10
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    • 1975
  • This paper presents an adaptive data compression algorithm for video data. The coling complexity due to the high correlation in the given data sequence is alleviated by coding the difference data, sequence rather than the data sequence itself. The adaptation to the nonstationary statistics of the data is confined within a code set, which consists of two constant length cades and six modified Shannon.Fano codes. lt is assumed that the probability distributions of tile difference data sequence and of the data entropy are Laplacian and Gaussion, respectively. The adaptive coding performance is compared for two code selection criteria: entropy and $P_r$[difference value=0]=$P_0$. It is shown that data compression ratio 2 : 1 is achievable with the adaptive coding. The gain by the adaptive coding over the fixed coding is shown to be about 10% in compression ratio and 15% in code efficiency. In addition, $P_0$ is found to he not only a convenient criterion for code selection, but also such efficient a parameter as to perform almost like entropy.

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Reversible Data Embedding Algorithm Using the Locality of Image and the Adjacent Pixel Difference Sequence (영상의 지역성과 인접 픽셀 차분 시퀀스를 이용하는 가역 데이터 임베딩 기법)

  • Jung, Soo-Mok
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.9 no.6
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    • pp.573-577
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    • 2016
  • In this paper, reversible data embedding scheme was proposed using the locality of image and the adjacent pixel difference sequence. Generally, locality exists in natural image. The proposed scheme increases the amount of embedding data and enables data embedding at various levels by applying a technique of predicting adjacent pixel values using image locality to an existing technique APD(Adjacent Pixel Difference). The experimental results show that the proposed scheme is very useful for reversible data embedding.

LINEAR ISOMORPHIC EULER FRACTIONAL DIFFERENCE SEQUENCE SPACES AND THEIR TOEPLITZ DUALS

  • RAJ, KULDIP;AIYUB, M.;SAINI, KAVITA
    • Journal of applied mathematics & informatics
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    • v.40 no.3_4
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    • pp.657-668
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    • 2022
  • In the present paper we introduce and study Euler sequence spaces of fractional difference and backward difference operators. We make an effort to prove that these spaces are BK-spaces and linearly isomorphic. Further, Schauder basis for Euler fractional difference sequence spaces $e^{\varsigma}_{0,p}({\Delta}^{(\tilde{\beta})},\;{\nabla}^m)$ and $e^{\varsigma}_{c,p}({\Delta}^{(\tilde{\beta})},\;{\nabla}^m)$ are also elaborate. In addition to this, we determine the 𝛼-, 𝛽- and 𝛾- duals of these spaces.