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Yayın A new method to represent speech signals via predefined signature and envelope sequences(Hindawi Publishing Corporation, 2007) Güz, Ümit; Gürkan, Hakan; Yarman, Bekir Sıddık BinboğaA novel systematic procedure referred to as "SYMPES" to model speech signals is introduced. The structure of SYMPES is based on the creation of the so-called predefined "signature S = {S(R)(n)} and envelope E = {E(K) (n)}" sets. These sets are speaker and language independent. Once the speech signals are divided into frames with selected lengths, then each frame sequence X(i)( n) is reconstructed by means of the mathematical form X(i)( n) = C(i)E(K) (n) S(R)(n). In this representation, C(i) is called the gain factor, S(R)(n) and E(K) (n) are properly assigned from the predefined signature and envelope sets, respectively. Examples are given to exhibit the implementation of SYMPES. It is shown that for the same compression ratio or better, SYMPES yields considerably better speech quality over the commercially available coders such as G. 726 (ADPCM) at 16 kbps and voice excited LPC-10E (FS1015) at 2.4 kbps.Yayın A new speech modeling method: SYMPES(IEEE, 2006) Güz, Ümit; Gürkan, Hakan; Yarman, Bekir Sıddık BinboğaIn this paper, the new method of speech modeling which is called SYMPES is introduced and it is compared with the commercially available methods. It is shown that for the same compression ratio or better, SYMPES yields considerably better hearing quality over the coders such as G.726 at 16 Kbps and voice excited LPC-10E of 2.4Kbps.Yayın A novel fast algorithm for speech and audio coding(IEEE, 2007) Güz, Ümit; Gürkan, Hakan; Yarman, Bekir Sıddık BinboğaIn this work a new mathematical modeling approach is proposed for the representation of the speech and audio signals. This approach is based on the generation of the so called Predefined Signature Sequence (PSS) and Predefined Envelope Sequence (PES) Sets. After the generation process of the PSS and PES sets, they are clustered by effective k-means clustering algorithm and the PSS and PES are redefined by using these centroids. By using this approach, the drawbacks by means of the size of the sets, speed of the reconstruction process (computational complexity) which arise in the proposed methods previously are highly eliminated. In spite of these improvements, the initial results proved that, the quality of the reconstructed signals remains within the limitations of the acceptable hearing quality.Yayın A novel method to represent the speech signals by using language and speaker independent predefined functions sets(IEEE, 2004) Güz, Ümit; Gürkan, Hakan; Yarman, Bekir Sıddık BinboğaIn this paper a new modeling method of speech signals is introduced. The proposed method is based on the generation of the so-called Predefined Signature S={s(R)(t)} and Envelope Function E = {e(K)(t)} Sets (PSEFS). These function sets are independent of any speaker and any language. Once the speech signals are divided into frames with selected lengths, then each frame signal piece X-i(t) is synthesized by means of the mathematical form of x(i)(t)=C(i)e(K)(t)s(R)(t). In this representation, C-i is called the frame coefficient, s(R)(t) and e(K)(t) are properly assigned from the PSEFS respectively. It is shown that the proposed method provides fast reconstruction and substantial compression with acceptable hearing quality.Yayın Modeling of electrocardiogram signals using predefined signature and envelope vector sets(Hindawi Publishing Corporation, 2007) Gürkan, Hakan; Güz, Ümit; Yarman, Bekir Sıddık BinboğaA novel method is proposed to model ECG signals by means of "predefined signature and envelope vector sets (PSEVS)." On a frame basis, an ECG signal is reconstructed by multiplying three model parameters, namely, predefined signature vector (PSV)(R)," "predefined envelope vector (PEV)(K)," and frame-scaling coefficient (FSC). All the PSVs and PEVs are labeled and stored in their respective sets to describe the signal in the reconstruction process. In this case, an ECG signal frame is modeled by means of the members of these sets labeled with indices R and K and the frame-scaling coefficient, in the least mean square sense. The proposed method is assessed through the use of percentage root-mean-square difference (PRD) and visual inspection measures. Assessment results reveal that the proposed method provides significant data compression ratio (CR) with low-level PRD values while preserving diagnostic information. This fact significantly reduces the bandwidth of communication in telediagnosis operations. Copyright (c) 2007 Hakan Gurkan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.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.
