A new window based on exponential function

Avcı, Kemal; Nacaroğlu, Arif

doi:10.1109/rme.2008.4595727

Cited by 19 publications

(17 citation statements)

References 4 publications

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“…For discrete time, the Exponential window [5] is defined in the following equations in terms of uniformly spaced samples.…”

Section: Exponential Windowmentioning

confidence: 99%

“…Since the use of an inappropriate window can lead to corruption of the principal spectral parameters, hence it is important to consider the criteria by which the choice of data weighting window to be selected for optimum results [4]. Here we will observe the effects of "α α α α or m" in recently proposed adjustable windows based on the Exponential [5] and Cosine Hyperbolic [6] and Polynomial [7] Window Functions on the SNR of RADAR returns.…”

Section: Introductionmentioning

confidence: 98%

See 1 more Smart Citation

The Effect of Exponential/Cosine Hyperbolic/ Polynomial/ Kaiser Window Parameters Cg-Icg-Enbw-Sl on the SNR Improvement of MST Radar Signals

Reddy¹

2013

IJRET

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“…For discrete time, the Exponential window [5] is defined in the following equations in terms of uniformly spaced samples.…”

Section: Exponential Windowmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

The Effect of Exponential/Cosine Hyperbolic/ Polynomial/ Kaiser Window Parameters Cg-Icg-Enbw-Sl on the SNR Improvement of MST Radar Signals

Reddy¹

2013

IJRET

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“…In literature, many windows has been proposed [7][8][9][10][11][12][13][14][15][16]. Fixed windows control the mainlobe width since these windows have one independent parameter, namely, the window length.…”

Section: Introductionmentioning

confidence: 99%

“…Dolph-Chebyshev [3], Kaiser [9] and Saramaki [10] are most used windows in literature and these windows are window functions having two adjustable parameters. Other improved windows based on Kaiser window equation were given at [11,12]. DolphChebyshev window having two parameters provides the minimum mainlobe width for a specified maximum sidelobe level.…”

Section: Introductionmentioning

confidence: 99%

The Using of ANN at Design of Window Function Having Useful Spectral Parameters

KAYA

2016

Fifth International Conference on Advances in Computing, Electronics and Electrical Technology - CEET 2016

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Abstract-The window functions are proposed structures at many application areas. The windows with helping two or more independent parameters show useful spectral characteristic. Kaiser window has been used at many areas because of the fact that it has good characteristic specification such as mainlobe width and the ripple ratio for various applications but Kaiser window having two parameters cannot control the sidelobe roll-off ratio. The ultraspherical window having three independent parameters has better sidelobe rolloff ratio than other windows in literature. At work, the coefficients of a new window function that has side-lobe roll-off ratio characteristic of ultraspherical window and Kaiser window's main-lobe width and ripple ratio were obtained by helping of artificial neural networks (ANN). 3000 data are used for training and testing of ANN. Sixty-five percentage of these data was used for learning of ANN and thirty-five percentage of that was used for testing process. It was observed that between the desired values and the obtained values using ANN were good agreements. Hence, a new window having better mainlobe width ripple ratio and side lobe roll-off ratio than other windows in spectral parameters at literature was modeled with ANN.

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“…Providing new window functions (or simply as windows) is in interest, because they are widely used in digital signal processing applications, e.g., signal analysis and estimation, digital filter design and speech processing [1][2][3]. In literature many windows have been proposed [4][5][6][7][8][9][10][11][12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%