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Date of Conference: 16-19 May 2016 Conference Name: IEEE 24th Signal Processing and Communications Applications Conference, SIU 2016 In this paper, we study multi-class classification of tweets, where we introduce highly efficient dimensionality reduction techniques suitable for online processing of high dimensional feature vectors generated from freely-worded text. As for the real life case study, we work on tweets in the Turkish language, however, our methods are generic and can be used for other languages as clearly explained in the paper. Since we work on a real life application and the tweets are freely worded, we introduce text correction, normalization and root finding algorithms. Although text processing and classification are highly important due to many applications such as emotion recognition, advertisement selection, etc., online classification and regression algorithms over text are limited due to need for high dimensional vectors to represent natural text inputs. We overcome such limitations by showing that randomized projections and piecewise linear models can be efficiently leveraged to significantly reduce the computational cost for feature vector extraction from the tweets. Hence, we can perform multi-class tweet classification and regression in real time. We demonstrate our results over tweets collected from a real life case study where the tweets are freely-worded, e.g., with emoticons, shortened words, special characters, etc., and are unstructured. We implement several well-known machine learning algorithms as well as novel regression methods and demonstrate that we can significantly reduce the computational complexity with insignificant change in the classification and regression performance.

Date of Conference: 2-5 May 2018 In this paper, we study online nonlinear data regression and propose a highly efficient long short term memory (LSTM) network based architecture. Here, we also introduce on-line training algorithms to learn the parameters of the introduced architecture. We first propose an LSTM based architecture for data regression. To diminish the complexity of this architecture, we use an energy efficient operator (ef-operator) instead of the multiplication operation. We then factorize the matrices of the LSTM network to reduce the total number of parameters to be learned. In order to train the parameters of this structure, we introduce online learning methods based on the exponentiated gradient (EG) and stochastic gradient descent (SGD) algorithms. Experimental results demonstrate considerable performance and efficiency improvements provided by the introduced architecture.

25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEY, WOS: 000413813100148, Electrical harmonic is an important issue affecting power quality of electrical systems. Estimation of power harmonics are essential to design filters to be utilized in electrical power systems for reducing harmonics and their effects on the electrical power systems. In this study, a harmonic estimator based on differential evolution algorithm is proposed for harmonic estimation problems shown in power systems. Analyses of designed estimator are performed for two different experiments. In addition, performances of proposed estimator are compared with available results of the literature. The achieved results of this study showed that the proposed harmonic estimator in this paper is superior among previously reported ones., Turk Telekom, Arcelik A S, Aselsan, ARGENIT, HAVELSAN, NETAS, Adresgezgini, IEEE Turkey Sect, AVCR Informat Technologies, Cisco, i2i Syst, Integrated Syst & Syst Design, ENOVAS, FiGES Engn, MS Spektral, Istanbul Teknik Univ

25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEY WOS: 000413813100213 Superpixel based methods have recently shown success in scene segmentation and labeling. In scene labeling, a superpixel algorithm is used first to segment the image into visually consistent small regions; then several feature descriptors are computed and classification is performed for each superpixel. In this paper, Kernel Codebook Encoding (KCB) of superpixel features is proposed. In KCB feature vectors are mapped to multiple codewords in a soft manner, instead of the usual hard quantization. The weights assigned to the codewords are determined by a kernel distance function. KCB method is used for encoding of SIFT features in SuperParsing image parsing algorithm. The developed approach is tested on the SIFT Flow dataset consisting of 2,688 images and 33 classes, and achieves 2.7% increase in parsing accuracy over SuperParsing. Turk Telekom, Arcelik A S, Aselsan, ARGENIT, HAVELSAN, NETAS, Adresgezgini, IEEE Turkey Sect, AVCR Informat Technologies, Cisco, i2i Syst, Integrated Syst & Syst Design, ENOVAS, FiGES Engn, MS Spektral, Istanbul Teknik Univ

25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEY WOS: 000413813100519 Along with the widespread use of technology, there have been many studies on human-computer relation recently. Study of the effects of computer systems on human education can be shown as an example of this. In this paper, a reliable and real time tangible user interface system developed for the air drum game which is used both for game and computer based training programs is presented. A user can perform a play action in six different directions using electronic drum sticks. A developed algorithm detects the direction of moving stick by processing sensor data taken from these sticks. Information about the stick which is moved and its direction are sent to the sound system to play the sound file of the relevant drum instrument. In this way the user is presented with a realistic drum experience. The developed system has been tested by different users in real world and its performance has been reported. The results verify the reliability and usability of the electronic drum game. Turk Telekom, Arcelik A S, Aselsan, ARGENIT, HAVELSAN, NETAS, Adresgezgini, IEEE Turkey Sect, AVCR Informat Technologies, Cisco, i2i Syst, Integrated Syst & Syst Design, ENOVAS, FiGES Engn, MS Spektral, Istanbul Teknik Univ

25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEY, WOS: 000413813100592, In this paper, a study which automatically detects four open string notes of the violin from the recorded violin sounds is presented for the purpose of using in the beginner level violin education. First, in order to be able to analyze the violin sound recordings, it is necessary for the music piece to be segmented into the notes forming the music piece itself For this, it is necessary to correctly determine the starting times (onsets) of the notes. Because of the envelope characteristic that the violin sound has, it is more difficult to detect the note onset than other musical instrument sounds such as piano and guitar. By using the complex spectral difference method, the note onsets were determined, then by determining the fundamental frequency the note of the violin sound was found. The proposed system was applied to the open string sound tracks obtained from eight people by using the iPad-based professional recording system, and the results showed that the proposed system worked successfully., Turk Telekom, Arcelik A S, Aselsan, ARGENIT, HAVELSAN, NETAS, Adresgezgini, IEEE Turkey Sect, AVCR Informat Technologies, Cisco, i2i Syst, Integrated Syst & Syst Design, ENOVAS, FiGES Engn, MS Spektral, Istanbul Teknik Univ

25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEY, WOS: 000413813100200, In this paper, the performance of direct current informative subcarrier intensity modulation (DCI-SIM) which is proposed to enhance the power efficiency of subcarrier intensity modulation (SIM) is investigated in visible light communication. The BER performance of DCI-SIM is compared with SIM, pulse amplitude modulation (PAM) and, enhanced unipolar orthogonal frequency division multiplexing (eU-OFDM) for different spectral efficiencies. Using analytical derivations and simulation results, we show that the DCI-SIM is the most power efficient modulation technique among others, and that the power efficiency increases with the spectral efficiency. Furthermore, we optimize the constellation of 64-DCI-SIM and present the results., Turk Telekom, Arcelik A S, Aselsan, ARGENIT, HAVELSAN, NETAS, Adresgezgini, IEEE Turkey Sect, AVCR Informat Technologies, Cisco, i2i Syst, Integrated Syst & Syst Design, ENOVAS, FiGES Engn, MS Spektral, Istanbul Teknik Univ

25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEY, WOS: 000413813100430, Reverberation and multipath propagation affect the accuracy of time of flight (TOF) estimation in confined underwater medium. In this paper, time delay has been estimated by obtaining the transmitted signal and first echo signal from measured signal acquired by using a wideband transducer with 5 MHz central frequency. Cross-correlation (CC) and generalized cross-correlation (GCC) methods have been applied to the obtained signals and their performances have been compared. The results show that GCC method has better performance for time delay estimation in confined underwater medium where multipath propagation and reverberation are severe., Turk Telekom, Arcelik A S, Aselsan, ARGENIT, HAVELSAN, NETAS, Adresgezgini, IEEE Turkey Sect, AVCR Informat Technologies, Cisco, i2i Syst, Integrated Syst & Syst Design, ENOVAS, FiGES Engn, MS Spektral, Istanbul Teknik Univ

24th Signal Processing and Communication Application Conference (SIU) (2016 : Zonguldak, Turkey ), In this paper, we presented a novel shape recognition framework based on medial axis graph. After extracting medial axis graph of a shape, we constructed a multi-dimensional distribution by calculating distances of each branch node to all other branch nodes in the graph. Then similarity rates between these distributions is found by using a transportation-based distance function. Finally, we compared our results with results of similar works conducted in the past., Bu bildiride, orta eksen çizgeleri (medial axis graph) kullanılarak şekil tanıma alanında yeni bir yaklaşım sunulmaktadır. İskeletleri çıkartılan şekillerin çizgelerinde, tüm kritik noktaların diger kritik noktalara olan en kısa yol uzaklığı hesaplanarak her bir şekil için çok boyutlu bir dagılım oluşturulmuştur. Önerilen şekil tanıma platformunda bu dagılımlar üzerinde taşıma tabanlı bir uzaklık fonksiyonu kullanılarak şekiller arasındaki benzerlik oranı bulunmuştur. Son olarak alınan sonuçlar daha önceden yapılmış benzer çalışmaların sonuçlarıyla karşılaştırılarak önerilen yaklaşımın başarımı gösterilmiştir.

In this paper, a computationally efficient method is proposed for modeling the indoor visible light communications (VLC) channels using a non-sequential ray tracing technique. We created three dimensional realistic simulation environment to depict indoor scenarios specifying the geometry of the indoor environment, the objects inside, the reflection characteristics of the surface materials as well as the characteristics of the transmitter and receiver. We then compute the received optical power and the delay of direct/indirect rays which are used to obtain the channel impulse response (CIR). Finally, LMS (least mean squares) and RLS (recursive least squares) iterative channel equalization techniques which are wildly employed in traditional electrical wireless communications are tested at the receiver of the VLC system. Their convergence rates as well as impacts on the BER performances are investigated by determining the optimal control parameters of these algorithms. It is concluded that for the equalizer operating with its optimal parameters, the BER performances of the VLC systems are very sensitivie to the field of view (FOV) values.

24th Signal Processing and Communication Application Conference (SIU) (2016 : Zonguldak, TURKEY), Critical Infrastructure Security had always been an issue. With the technological advancements, there has been a continuous inflow of novel methods for critical infrastructure security. In this paper, design, implementation, and field tests of a novel critical infrastructure security system based on wireless sensor networks is presented.

24th Signal Processing and Communication Application Conference (SIU) -- MAY 16-19, 2016 -- Zonguldak, TURKEY, WOS: 000391250900110, In this paper, 11 different power quality disturbances were automatically detected by using statistical features with wavelet transform and norm entropy techniques. The best of the created features were selected with forward selection algorithm. Performance of classification algorithms, Support Vector Machines (SVM), Multi Layer Perceptron (MLP), k Nearest Neighbor (KNN) and random subspace KNN (Sub-KNN) which is an ensemble method, were examined. Consequently, the best classification accuracy of 99.3% was achieved by using Sub-KNN and it was appeared that compared to other methods, this algorithm was more robust against the noise., IEEE, Bulent Ecevit Univ, Dept Elect & Elect Engn, Bulent Ecevit Univ, Dept Biomed Engn, Bulent Ecevit Univ, Dept Comp Engn

Date of Conference: 16-19 May 2016 Conference Name: IEEE 24th Signal Processing and Communications Applications Conference, SIU 2016 In this paper, we offer and examine a new algorithm for sequential nonlinear regression problem. In this architecture, we use piecewise adaptive linear functions to find the nonlinear regression model sequentially. For more accurate and faster convergence, we combine a large class of piecewise linear functions. These piecewise linear functions are constructed by composing different adaptive linear functions, which are represented by the nodes of a lexicographical tree. With this tree structure, computational complexity of the algorithm is significantly reduced. To show the performance of the proposed algorithm, we present a simulation which is performed by using a well-known real data set.

In this paper, a new optical orthogonal frequency division multiplexing (OFDM) method is proposed for multiple-input multiple-output (MIMO) visible light communications (VLC) systems. In the new scheme, non-DC biased optical OFDM (NDC-OFDM) and optical spatial modulation (OSM) methods are combined to obtain a novel optical OFDM scheme which has a better error performance. The new scheme is named as non-DC biased optical spatial modulation OFDM (NDC-OSM-OFDM). It is shown via computer simulations that the proposed scheme achieves better bit error rate (BER) performance than DC-biased optical spatial modulation OFDM (OSM-OFDM-DC), asymmetrically clipped optical spatial modulation OFDM (OSM-OFDM-AC) and NDC-OFDM.

Compressed sensing theory shows that any signal which is defined as sparse in a given domain can be reconstructed using fewer linear projections instead of using all Nyquist-rate samples. In this paper, we investigate basis pursuit, matching pursuit, orthogonal matching pursuit and compressive sampling matching pursuit algorithms, which are basic compressed sensing based algorithms, and present performance curves in terms of mean squared error for various parameters including signal-to-noise ratio, sparsity and number of measurements with regard to mean squared error. In addition, accuracy of estimation performances has been supported with theoretical lower bounds (Cramer-Rao lower bound and deterministic lower mean squared error). Considering estimation performances, compressive sampling matching pursuit yields the best results unless the signal has a non-sparse structure.