Browsing by Subject "Performance analysis"

Now showing 1 - 20 of 20

Open Access
An evaluation of transaction management issues in mobile real-time database systems
(1998-01) Kayan, Ersan
The integration of issues from real-time database systems and mobile computing systems is a new research area that aims to provide support for real-time requirements of database applications in a mobile computing environment. Due to certain constraints of a mobile computing environment, such as resource-poor mobile computers, low-bandwidth and unreliable wireless links, and mobility of users/computers, various research issues in traditional real-time database systems need to be reconsidered. In this thesis, we investigate some of these issues using a detailed simulation model of a mobile real-time database management system. We propose a transaction execution model with two alternative execution strategies and evaluate the performance of the system considering various mobile system characteristics. Performance results are provided in terms of the fraction of transaction that satisfy their deadlines.
Open Access
Clutter detection algorithms for airborne pulse-Doppler radar
(IEEE, 2010) Güngör, Ahmet; Gezici, Sinan
Clutter detection is an important stage of target detection. Clutter may not always appear around zero Doppler frequency when realistic terrain models and moving platforms are considered. Two algorithms developed for clutter detection using range-Doppler matrix elements and their performance analysis are presented in this paper. The first algorithm has higher error rates but lower computational complexity whereas the second one has lower error rates but higher computational complexity. The algorithms detect clutter position by filtering range-Doppler matrix elements via non-linear filters. ©2010 IEEE.
Open Access
Compressive sensing-based robust off-the-grid stretch processing
(Institution of Engineering and Technology, 2017) Ilhan, I.; Gurbuz, A. C.; Arıkan, Orhan
Classical stretch processing (SP) obtains high range resolution by compressing large bandwidth signals with narrowband receivers using lower rate analogue-to-digital converters. SP achieves the resolution of the large bandwidth signal by focusing into a limited range window, and by deramping in the analogue domain. SP offers moderate data rate for signal processing for high bandwidth waveforms. Furthermore, if the scene in the examined window is sparse, compressive sensing (CS)-based techniques have the potential to further decrease the required number of measurements. However, CS-based reconstructions are highly affected by model mismatches such as targets that are off-the-grid. This study proposes a sparsity-based iterative parameter perturbation technique for SP that is robust to targets off-the-grid in range or Doppler. The error between reconstructed and actual scenes is measured using Earth mover's distance metric. Performance analyses of the proposed technique are compared with classical CS and SP techniques in terms of data rate, resolution and signal-to-noise ratio. It is shown through simulations that the proposed technique offers robust and high-resolution reconstructions for the same data rate compared with both classical SP- and CS-based techniques.
Open Access
Decoding strategies at the relay with physical-layer network coding
(Institute of Electrical and Electronics Engineers, 2012) Bhat, U.; Duman, T. M.
A two-way relay channel is considered where two users exchange information via a common relay in two transmission phases using physical-layer network coding (PNC). We consider an optimal decoding strategy at the relay to decode the network coded sequence during the first transmission phase, which is approximately implemented using a list decoding (LD) algorithm. The algorithm jointly decodes the codewords transmitted by the two users and sorts the L most likely pair of sequences in the order of decreasing a-posteriori probabilities, based on which, estimates of the most likely network coded sequences and the decoding results are obtained. Using several examples, it is observed that a lower complexity alternative, that jointly decodes the two transmitted codewords, has a performance similar to the LD based decoding and offers a near-optimal performance in terms of the error rates corresponding to the XOR of the two decoded sequences. To analyze the error rate at the relay, an analytical approximation of the word-error rate using the joint decoding (JD) scheme is evaluated over an AWGN channel using an approach that remains valid for the general case of two users adopting different codebooks and using different power levels. We further extend our study to frequency selective channels where two decoding approaches at the relay are investigated, namely; a trellis based joint channel detector/physical-layer network coded sequence decoder (JCD/PNCD) which is shown to offer a near-optimal performance, and a reduced complexity channel detection based on a linear receiver with minimum mean squared error (MMSE) criterion which is particularly useful where the number of channel taps is large.
Open Access
A discussion on homography between stationary multi-camera systems and the soccer field model
(IEEE, 2012) Baysal, Sermetcan; Duygulu, Pınar; Kayalar, Ceren
Computer vision based athlete tracking systems use different methods to segment players from the background and then track them automatically throughout the video. It is insufficient to know a player's position on the image plane if we want to extract performance analysis of the player. Furthermore, image plane coordinates need to be transformed to real world coordinates representing the position of the player on the field. Knowing that the soccer field is planar, the mapping between the world coordinate system and the image coordinate system can be described by a planar homography. In this paper, we provide a discussion on homography calculations between a three-camera player tracking system and the real world soccer field model. © 2012 IEEE.
Open Access
Energy-Optimum throughput and carrier sensing rate in csma-based wireless networks
(IEEE, 2014) Koseoglu, M.; Karasan, E.
We propose a model for the energy consumption of a node as a function of its throughput in a wireless CSMA network. We first model a single-hop network, and then a multi-hop network. We show that operating the CSMA network at a high throughput is energy inefficient since unsuccessful carrier sensing attempts increase the energy consumption per transmitted bit. Operating the network at a low throughput also causes energy inefficiency because of increased sleeping duration. Achieving a balance between these two opposite operating regimes, we derive the energy-optimum carrier-sensing rate and the energy-optimum throughput which maximize the number of transmitted bits for a given energy budget. For the single-hop case, we show that the energy-optimum total throughput increases as the number of nodes sharing the channel increases. For the multi-hop case, we show that energy-optimum throughput decreases as the degree of the conflict graph corresponding to the network increases. For both cases, the energy-optimum throughput reduces as the power required for carrier-sensing increases. The energy-optimum throughput is also shown to be substantially lower than the maximum throughput and the gap increases as the degree of the conflict graph increases for multi-hop networks. © 2002-2012 IEEE.
Open Access
Equivalent circuit-based analysis of CMUT cell dynamics in arrays
(IEEE, 2013) Oğuz, H. K.; Atalar, Abdullah; Köymen, Hayrettin
Capacitive micromachined ultrasonic transducers (CMUTs) are usually composed of large arrays of closely packed cells. In this work, we use an equivalent circuit model to analyze CMUT arrays with multiple cells. We study the effects of mutual acoustic interactions through the immersion medium caused by the pressure field generated by each cell acting upon the others. To do this, all the cells in the array are coupled through a radiation impedance matrix at their acoustic terminals. An accurate approximation for the mutual radiation impedance is defined between two circular cells, which can be used in large arrays to reduce computational complexity. Hence, a performance analysis of CMUT arrays can be accurately done with a circuit simulator. By using the proposed model, one can very rapidly obtain the linear frequency and nonlinear transient responses of arrays with an arbitrary number of CMUT cells. We performed several finite element method (FEM) simulations for arrays with small numbers of cells and showed that the results are very similar to those obtained by the equivalent circuit model.
Open Access
Infinite-and finite-buffer Markov fluid queues: a unified analysis
(Applied Probability Trust, 2004) Akar, N.; Sohraby, K.
In this paper, we study Markov fluid queues where the net fluid rate to a single-buffer system varies with respect to the state of an underlying continuous-time Markov chain. We present a novel algorithmic approach to solve numerically for the steady-state solution of such queues. Using this approach, both infinite- and finite-buffer cases are studied. We show that the solution of the infinite-buffer case is reduced to the solution of a generalized spectral divide-and-conquer (SDC) problem applied on a certain matrix pencil. Moreover, this SDC problem does not require the individual computation of any eigenvalues and eigenvectors. Via the solution for the SDC problem, a matrix-exponential representation for the steady-state queue-length distribution is obtained. The finite-buffer case, on the other hand, requires a similar but different decomposition, the so-called additive decomposition (AD). Using the AD, we obtain a modified matrix-exponential representation for the steady-state queue-length distribution. The proposed approach for the finite-buffer case is shown not to have the numerical stability problems reported in the literature.
Open Access
Investigation and comparison of the preprocessing algorithms for microarray analysis for robust gene expression calculation and performance analysis of technical replicates
(IEEE, 2006) İlk, H. G.; İlk, Ö.; Konu, Özlen; Özdağ, H.
Preprocessing of microarray data involves the necessary steps of background correction, normalization and summarization of the raw intensity data obtained from cDNA or oligo-arrays before statistical analysis. Several algorithms, namely RMA, dChip, and MAS5 exist for the preprocessing of Affymetrix microarray data. Previous studies have identified RMA as one of most accurate algorithms while MAS5 was characterized with lower accuracy and sensitivity levels. In this study, performance of different preprocessing algorithms have been compared in terms of ROC characteristics of pairwise intensity differences of microarray replicates. Our findings indicated that all three algorithms predicted in similar order the quality of the technical replicates obtained from a selected set of latin square experiments [1]. On the other hand, RMA exhibited higher performance in terms of accuracy by maximizing the area under the receiver operating curve. The proposed method also is useful for detection of global and/or local artifacts associated within the technical replicas of a microarray experiment. Therefore this study is unique in the sense that it provides an extensive investigation and comparison of preprocessing algorithms and proposes a novel method for the detection and identification of fine technical replicate pair.
Open Access
Parallel stochastic gradient descent on multicore architectures
(2020-09) Gülcan, Selçuk
The focus of the thesis is efficient parallelization of the Stochastic Gradient Descent (SGD) algorithm for matrix completion problems on multicore architectures. Asynchronous methods and block-based methods utilizing 2D grid partitioning for task-to-thread assignment are commonly used approaches for sharedmemory parallelization. However, asynchronous methods can have performance issues due to their memory access patterns, whereas grid-based methods can suffer from load imbalance especially when data sets are skewed and sparse. In this thesis, we first analyze parallel performance bottlenecks of the existing SGD algorithms in detail. Then, we propose new algorithms to alleviate these performance bottlenecks. Specifically, we propose bin-packing-based algorithms to balance thread loads under 2D partitioning. We also propose a grid-based asynchronous parallel SGD algorithm that improves cache utilization by changing the entry update order without affecting the factor update order and rearranging the memory layouts of the latent factor matrices. Our experiments show that the proposed methods perform significantly better than the existing approaches on shared-memory multi-core systems.
Open Access
Performance analysis of code-multiplexed transmitted-reference ultra-wideband systems
(IEEE, 2011) Tutay, Mehmet Emin; Gezici, Sinan; Poor H.V.
In code-multiplexed transmitted-reference (CM-TR) ultra-wideband (UWB) systems, data signals and reference signals are transmitted using two distinct orthogonal codes. In this way, performance improvements and/or implementation advantages are obtained compared to transmitted-reference (TR) and frequency-shifted reference (FSR) ultra-wideband (UWB) systems. In this study, performance of CM-TR systems is investigated, and probability of error expressions are obtained. For the single user case, a closed-form expression for the exact probability of error is derived, whereas a Gaussian approximation, the accuracy of which depends on the number of frames per symbol, is considered for the multiuser case. Also, the maximum likelihood detector is derived, and numerical examples are presented. © 2011 IEEE.
Open Access
Performance analysis of concatenated coding schemes
(1999) Akkor, Gün
In this thesis we concentrate on finding tight upperbounds on the output error rate of concatenated coding systems with binary convolutional inner codes and Reed-Solomon outer codes. Performance of such a system can be estimated by first calculating the error rate of the inner code and then by evaluating the outer code performance. Two new methods are proposed to improve the classical union bound on convolutional codes. The methods provide better error estimates in the low signal-to-noise ratio (SNR) region where the union bound increases abruptly. An ideally-interleaved system performance is evaluated based on the convolutional code bit error rate estimates. Results show that having better estimates for the inner code performance improves the estimates on the overall system performance. For the analysis of a non-interleaved system, a new model based on a Markov Chain representation of the system is proposed. For this purpose, distribution of errors between the inner and outer decoding stages is obtained through simulation. Markov Chain parameters are determined from the error distribution and output error rate is obtained by analyzing the behavior of the model. The model estimates the actual behavior over a considerable SNR range. Extensive computer simulations are run to evaluate the accuracy of these methods.
Open Access
Performance analysis of scalar diffusion strategy over distributed network
(IEEE, 2014) Sayın, Muhammed Ö.; Kozat, Süleyman Serdar
In this paper, we present a complete performance analysis of the scalar diffusion strategies over distributed networks. Scalar diffusion strategies are based on the diffusion implementation and adaptive extraction of the information from the diffusion data which is compressed into a scalar. This strategy require significantly less communication load while achieving similar performance with the full information exchange configuration. Here, we provide the transient and steady-state analysis of the scalar diffusion strategies for Gaussian regressors. Finally, in the numerical examples, we demonstrate that the theoretical results match with the simulation results.
Open Access
Performance analysis of turbo codes over Nakagami-m fading channels with impulsive noise
(IEEE, 2007) Ali, Syed Amjad; İnce, E. A.
The statistical characteristics of impulsive noise differ greatly from those of Gaussian noise. Hence, the performance of conventional decoders, optimized for AWGN channels is not promising in non-Gaussian environments. In order to achieve improved performance in impulsive environments the decoder structure needs to be adapted in accordance with the impulsive noise model. This paper provides performance analysis of turbo codes over fully interleaved Nakagami-m fading channels with Middleton's additive white Class-A impulsive noise (MAWCAIN). Simulation results for memoryless Nakagami-m fading channels under coherent BPSK signaling are provided for the cases of ideal channel state information (ICSI) and no channel state information (NCSI) at the decoder. As in the 3GPP UMTS forward link an eight state turbo encoder having (1, 13/15, 13/15) generator polynomial is used throughout the analysis. The novelty of this work lies in the fact that this is an initial attempt to provide a detailed analysis of turbo codes over Nakagami-m fading channels with impulsive noise rather than fading channels with AWGN. © 2007 IEEE.
Open Access
Performance analysis of two-level forward error correction for lostcell recovery in ATM networks
(IEEE, 1995-04) Oğuz, Nihat Cem; Ayanoğlu, E.
The major source of errors in B-ISDN/ATM systems is expected to be buffer overflow during congested conditions, resulting in ATM cell losses which degrade the quality of service. It has been shown by many authors that the performance of the end-to-end system can be made much less sensitive to cell loss by means of forward error correction. This paper discusses the use of a two-level forward error correction scheme for virtual channel and virtual path connections in ATM networks. The scheme exploits simple block coding and code interleaving simultaneously. The simple block, interleaved, and joint coding schemes are studied and analyzed by using a novel and accurate discrete-time analytical method which enables the burstiness of cell losses be captured precisely. Detailed performance calculations, which indicate that it is possible to reduce the cell loss rate by several orders of magnitude over a wide range of network load for various traffic conditions, are discussed, and compared with simulation results. The comparisons show that the method is very accurate for bursty traffic. The advantages of the three coding techniques are quantified for different traffic characteristics and scenarios © Copyright 2009 IEEE - All Rights Reserved.
Open Access
The performance comparison of different training strategies for reinforcement learning on DeepRTS
(IEEE, 2022-08-29) Şahin, Safa Onur; Yücesoy, Veysel
In this paper, we train reinforcement learning agents on the game of DeepRTS under different training strategies, which are i) training against rule based agents, ii) self-training and iii) training by adversarial attack to another agent. We perform certain modifications on the DeepRTS game and the reinforcement learning framework to make it closer to real life decision making problems. For this purpose, we allow agents take macro actions based on human heuristics, where these actions may last multiple time steps and the durations for these actions may differ from each other. In addition, the agents simultaneously take actions for each available unit at a time step. We train the reinforcement learning based agents under three different training strategies and we provide a detailed performance analysis of these agents against several reference agents.
Open Access
Robust adaptive algorithms for underwater acoustic channel estimation and their performance analysis
(Elsevier Inc., 2017) Kari, D.; Marivani, I.; Khan, F.; Sayin, M. O.; Kozat, S. S.
We introduce a novel family of adaptive robust channel estimators for highly challenging underwater acoustic (UWA) channels. Since the underwater environment is highly non-stationary and subjected to impulsive noise, we use adaptive filtering techniques based on minimization of a logarithmic cost function, which results in a better trade-off between the convergence rate and the steady state performance of the algorithm. To improve the convergence performance of the conventional first and second order linear estimation methods while mitigating the stability issues related to impulsive noise, we intrinsically combine different norms of the error in the cost function using a logarithmic term. Hence, we achieve a comparable convergence rate to the faster algorithms, while significantly enhancing the stability against impulsive noise in such an adverse communication medium. Furthermore, we provide a thorough analysis for the tracking and steady-state performances of our proposed methods in the presence of impulsive noise. In our analysis, we not only consider the impulsive noise, but also take into account the frequency and phase offsets commonly experienced in real life experiments. We demonstrate the performance of our algorithms through highly realistic experiments performed on accurately simulated underwater acoustic channels.
Open Access
Robust adaptive algorithms for underwater acoustic channel estimation and their performance analysis
(2017-09) Marivani, Iman
We introduce a novel family of adaptive robust channel estimators for highly chal- lenging underwater acoustic (UWA) channels. Since the underwater environment is highly non-stationary and subjected to impulsive noise, we use adaptive ltering techniques based on minimization of a logarithmic cost function, which results in a better trade-off between the convergence rate and the steady state performance of the algorithm. To improve the convergence performance of the conventional rst and second order linear estimation methods while mitigating the stability issues related to impulsive noise, we intrinsically combine different norms of the error in the cost function using a logarithmic term. Hence, we achieve a com- parable convergence rate to the faster algorithms, while signi cantly enhancing the stability against impulsive noise in such an adverse communication medium. Furthermore, we provide a thorough analysis for the tracking and steady-state performances of our proposed methods in the presence of impulsive noise. In our analysis, we not only consider the impulsive noise, but also take into account the frequency and phase offsets commonly experienced in real life experiments. We demonstrate the performance of our algorithms through highly realistic experi- ments performed on accurately simulated underwater acoustic channels.
Open Access
Robust controller design for AQM and H∞-performance analysis
(Springer, 2005) Yan, P.; Özbay, Hitay
Active Queue Management (AQM) has recently been proposed in [1] to support the end-to-end congestion control for TCP traffic regulation on the Internet. For the purpose of alleviating congestion for IP networks and providing some notion of quality of service (QoS), the AQM schemes are designed to improve the Internet applications. Earliest efforts on AQM (e.g. RED in [2]) are essentially heuristic without systematic analysis. The dynamic models of TCP ([9, 12]) make it possible to design AQM using feedback control theory. We refer to [11] for a general review of Internet congestion control.
Open Access
Rule based segmentation and subject identification using fiducial features and subspace projection methods
(Academy Publisher, 2007) Ince, E. A.; Ali, S. A.
This paper describes a framework for carrying out face recognition on a subset of standard color FERET database using two different subspace projection methods, namely PCA and Fisherfaces. At first, a rule based skin region segmentation algorithm is discussed and then details about eye localization and geometric normalization are given. The work achieves scale and rotation invariance by fixing the inter ocular distance to a selected value and by setting the direction of the eye-to-eye axis. Furthermore, the work also tries to avoid the small sample space (S3) problem by increasing the number of shots per subject through the use of one duplicate set per subject. Finally, performance analysis for the normalized global faces, the individual extracted features and for a multiple component combination are provided using a nearest neighbour classifier with Euclidean and/or Cosine distance metrics.