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Publication Metadata only A limited memory BFGS based unimodular sequence design algorithm for spectrum-aware sensing systems(IEEE-inst Electrical Electronics Engineers inc, 2022) N/A; Savcı, Kubilay; PhD Student; Graduate School of Sciences and Engineering; N/AUnimodular sequences with good correlation and spectral properties are desirable in numerous applications such as active remote sensing and communication systems. therefore, designing sequences with stopband and correlation sidelobe constraints has gained a lot of attention in the last few decades. in this paper, we propose a fast and efficient iterative algorithm to design unimodular and sparse frequency waveforms with low aperiodic/periodic autocorrelation sidelobes and desired stopband properties. in our approach, the bi-objective optimization problem which minimizes both the integrated sidelobe level (ISL) of the autocorrelation function and the power density in the spectral stopbands is first turned into an unconstrained single objective optimization problem and then is treated as a nonlinear large-scale problem. for the solution of the problem, we develop an algorithm based on Limited Memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) Quasi-Newton optimization method. Unlike most gradient based algorithms which employ line searches to deduce the step length, owing to L-BFGS method, unit step length is taken as a general rule to avoid the cost of computation at every iteration with very few exceptions. the calculation of gradient is based on Fast Fourier Transform and Hadamard product operations and thus the algorithm is fast and computationally efficient. Moreover, the algorithm is space efficient and its low-memory feature makes it possible to generate long sequences. Several numerical examples are presented to validate the efficacy of the proposed method and to show its superiority over other state-of-art algorithms.Publication Metadata only A phonetic classification for throat microphone enhancement(IEEE, 2014) N/A; Department of Computer Engineering; Turan, Mehmet Ali Tuğtekin; Erzin, Engin; PhD Student; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 34503In this analysis paper, we investigate the effect of phonetic clustering based on place and manner of articulation for the enhancement of throat-microphone speech through spectral envelope mapping. Place of articulation (PoA) and manner of articulation (MoA) dependent GMM-based spectral envelope mapping schemes have been investigated using the reflection coefficient representation of the linear prediction model. Reflection coefficients are expected to localize mapping performance within the concatenation of lossless tubes model of the vocal tract. In experimental studies, we evaluate spectral mapping performance within clusters of the PoA and MoA using the log-spectral distortion (LSD) and as function of reflection coefficient mapping using the mean-square error distance. Our findings indicate that highest degradations after the spectral mapping occur with stops and liquids of the MoA, and velar and alveolar classes of the PoA. The MoA classification attains higher improvements than the PoA classification.Publication Metadata only Adaptive radial basis function neural network based tracking control of Van der Pol oscillator(Institute of Electrical and Electronics Engineers (IEEE), 2017) Zohaib, Adil; Hussain, Syed Shahzad; N/A; N/A; Ulasyar, Abasin; Zad, Haris Sheh; Researcher; PhD Student; Manufacturing and Automation Research Center (MARC); N/A; Graduate School of Sciences and Engineering; N/A; N/AIn this paper an online adaptive Radial Basis Function (RBF) controller is designed and simulated for the tracking control of Van der Pol oscillator. Van der pol oscillator is a nonlinear oscillator which is used for the modeling of various laser, mechanical and electrical oscillatory systems. The control and adaptive laws for the RBF controller are designed based on the neural network approximation. Lyapunov stability criterion is used in order to analyze the stability of the designed control and adaptive laws. Matlab/Simulink tool is used for the simulation of the designed adaptive controller for the tracking control of Van der Pol oscillator. The designed controller performance is tested with the uncertain system parameters and in the presence of disturbance in the system. The results of simulation show better reference tracking of the oscillator with the designed adaptive controller having good set speed and control accuracy. The designed controller has good robustness against the system perturbations and disturbances.Publication Metadata only Affect burst recognition using multi-modal cues(IEEE Computer Society, 2014) N/A; N/A; Department of Computer Engineering; Department of Computer Engineering; Department of Computer Engineering; Türker, Bekir Berker; Marzban, Shabbir; Erzin, Engin; Yemez, Yücel; Sezgin, Tevfik Metin; PhD Student; Master Student; Faculty Member; Faculty Member; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; College of Engineering; N/A; N/A; 34503; 107907; 18632Affect bursts, which are nonverbal expressions of emotions in conversations, play a critical role in analyzing affective states. Although there exist a number of methods on affect burst detection and recognition using only audio information, little effort has been spent for combining cues in a multi-modal setup. We suggest that facial gestures constitute a key component to characterize affect bursts, and hence have potential for more robust affect burst detection and recognition. We take a data-driven approach to characterize affect bursts using Hidden Markov Models (HMM), and employ a multimodal decision fusion scheme that combines cues from audio and facial gestures for classification of affect bursts. We demonstrate the contribution of facial gestures to affect burst recognition by conducting experiments on an audiovisual database which comprise speech and facial motion data belonging to various dyadic conversations.Publication Restricted Communication theoretical foundations of nervous system(Koç University, 2018) Ramezani, Hamideh; Akan, Özgür Barış; 0000-0003-2523-3858; Koç University Graduate School of Sciences and Engineering; Electrical and Electronics Engineering; 6647Publication Metadata only Complaint detection and classification of customer reviews(IEEE, 2021) Bayrak, Ahmet Tuğrul; Yıldız, Eray; Özbek, Eyüp Erkan; Türker, Bekir Berker; PhD Student; Graduate School of Sciences and Engineering; N/AIn a world where competition and technology usage increase consistently, customer satisfaction has become important for companies. In this study, the customer reviews, obtained from the results of the surveys that are made via different channels, are analyzed and when a problem is detected, a quick solution is aimed. For the complaint detection and classification on the customer reviews process, long short-term memory, which is a recurrent neural network, is applied. A data set from the tourism industry is labelled to carry out the proposed method. The results retrieved on performing the method on the data, which is relatively larger than the similar works in literature, are acceptable and the proposed model works in real-time.Publication Metadata only Compressed training adaptive MIMO equalization(IEEE, 2016) N/A; Department of Electrical and Electronics Engineering; Yılmaz, Baki Berkay; Erdoğan, Alper Tunga; Researcher; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 41624This article proposes an adaptive equalization framework for flat fading multi-input multi-output(MIMO) systems, where the main goal is to significantly reduce the number of training symbols. The proposed approach exploits the special boundedness property of digital communication signals along with training symbols to adapt receiver equalizer filter. The corresponding framework is built upon some convex settings where the infinity norm is used to utilize the special constellation structure for the efficient adaptation process. As a fundamental result, through the duality between l(infinity) and l(1) norms, the proposed approach establishes an interesting link between adaptive equalization problem and compressed sensing problems. Using this link, the aim of the proposed optimization settings can be viewed as achieving the desired sparseness of the perfect equalization channel with compressed amount of training symbols. Based on this connection, we can prescribe that the training size is on the order of logarithm of the number of sources without any prior sparsity assumption on the wireless channel model. This promises a significant reduction in training symbols especially for the base stations employing very large number of antennas such as Massive MIMO applications. The numerical examples verify the analytical results and demonstrate the practical benefits of the proposed approach.Publication Metadata only Cooperative MIMO-OFDM based inter-vehicular visible light communication using brake lights(Elsevier, 2018) Narmanlıoğlu, Omer; T; Uysal, Murat; N/A; Department of Electrical and Electronics Engineering; Turan, Buğra; Ergen, Sinem Çöleri; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 7211Inter-vehicular connectivity to enhance road safety and support highly autonomous driving is increasingly becoming popular. Despite the prevalent works on radio-frequency (RF) based vehicular communication schemes, visible light communication (VLC) is considered to be a promising candidate for vehicular communications due to its low complexity and RF interference-free nature. Deployment of multiple light emitting diodes (LEDs) enables multiple-input multiple-output (MIMO) transmission in the context of vehicular VLC. This paper investigates applicability of both point-to-point (direct) vehicular VLC and decode-and-forward relaying based cooperative vehicular VLC including relay terminals between source and destination terminals to enhance road safety based on real world measurements. We consider direct current biased optical orthogonal frequency division multiplexing (DCO-OFDM) based MIMO transmission scheme and evaluate the performances of different MIMO modes including repetition code (RC) and spatial multiplexing (SM), different modulation orders with different transmitter receiver selection mechanisms to support line-of-sight (LoS) and beyond LoS multi-hop vehicular VLC. The results reveal that the selection of the closest transmitters to the receivers provides better performance due to high signal-to-noise-ratio requirements for RC mode whereas SM suffers from channel correlation. Usage of all possible transmitters does not always yield better performance due to the power division at the transmitter side. on the other hand, the performance of RC shows more degradation on higher-order modulations that are required to yield the same throughput with SM. Therefore, considering the higher order modulation requirement for RC based VLC, SM is concluded to be a favorable MIMO scheme for cooperative vehicular VLC. We further demonstrate the benefits of multi-hop transmission over direct transmission with respect to different number of relay vehicles as a consequence of varying inter-vehicular distances between source and destination vehicles.Publication Metadata only Correction to: online failure diagnosis in interdependent networks (Operations Research Forum, (2021), 2, 1, (10), 10.1007/s43069-021-00055-2)(Springer International Publishing, 2021) Akbari, Vahid; N/A; Shiri, Davood; PhD Student; Graduate School of Sciences and Engineering; N/AN/APublication Metadata only Data-driven anomaly detection in autonomous platoon(Institute of Electrical and Electronics Engineers (IEEE), 2018) N/A; Department of Electrical and Electronics Engineering; Department of Computer Engineering; Uçar, Seyhan; Ergen, Sinem Çöleri; Özkasap, Öznur; PhD Student; Faculty Member; Faculty Member; Department of Electrical and Electronics Engineering; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; 7211; 113507Technology brings autonomous vehicles into a reality where vehicles cruise themselves without human input. Vehicular platoon, on the other hand, is a group of autonomous vehicles that are organized into close proximity through wireless communication. In an autonomous platoon, vehicles cooperatively send data to each other to adjust their speed and distance to the leader, the first vehicle in the platoon. However, this cooperative data exchange can lead to security risks. A misbehaving platoon member could alter the data packets which may cause platoon instability. Therefore, identifying the modified packets has become an important requirement. In this paper, we investigate data-driven anomaly detection mechanisms for the autonomous platoon. We propose a novel statistical learning based technique to detect the modified packets and misbehaving vehicles. We demonstrate that the distance change to the leader would be sufficient to detect anomalies and misbehavior.