Pub Date : 2022-05-15DOI: 10.1109/SIU55565.2022.9864701
A. Utku, Umit Can
Air pollution affects human life negatively, especially in terms of health, and causes the death of millions of people every year. Today, air pollution in many regions is still above the limits indicated by the World Health Organization. In this study, the prediction of the rate of PM2.5, which is an important air pollutant, in the Beijing region of China is emphasized. For this purpose, weather prediction models were created using Random Forest Algorithm, Support Vector Regression, XGBoost and K-Nearest Neighbor Algorithm, which are popular machine learning algorithms, and the results were compared using various metrics. The best prediction result in all the metrics used was obtained with the Support Vector Regression method.
{"title":"Machine Learning-Based A Comparative Analysis for Air Quality Prediction","authors":"A. Utku, Umit Can","doi":"10.1109/SIU55565.2022.9864701","DOIUrl":"https://doi.org/10.1109/SIU55565.2022.9864701","url":null,"abstract":"Air pollution affects human life negatively, especially in terms of health, and causes the death of millions of people every year. Today, air pollution in many regions is still above the limits indicated by the World Health Organization. In this study, the prediction of the rate of PM2.5, which is an important air pollutant, in the Beijing region of China is emphasized. For this purpose, weather prediction models were created using Random Forest Algorithm, Support Vector Regression, XGBoost and K-Nearest Neighbor Algorithm, which are popular machine learning algorithms, and the results were compared using various metrics. The best prediction result in all the metrics used was obtained with the Support Vector Regression method.","PeriodicalId":115446,"journal":{"name":"2022 30th Signal Processing and Communications Applications Conference (SIU)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116025041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-15DOI: 10.1109/SIU55565.2022.9864712
Burak Yilmaz, A. Dolma
Losses and dispersions, which constitute the most important transmission characteristics of the fiber, are undesirable and should be avoided in communication. In the study, the analysis of environmental and material-related losses in fiber transmission lines was made. As a result of the analysis, the causes of the losses were emphasized, the graphs of the losses in the fiber depending on the wavelength were obtained, and a study was carried out to calculate the loss amounts approximately. In the second stage of the study, dispersion and its types, which are the most important determining factors that determine the transmission speed and distance of the fiber, are briefly explained, and a simulation in single-mode fiber is prepared in order to better display the dispersion by using a computer program. In the simulation, the effect of loss and dispersion on 4 light pulses was investigated. As a result of the studies, it has been determined how the bit error rate (BER) occurs in fiber optic communication. Finally, the applications that will minimize the dispersion and loss in the fiber are emphasized.
{"title":"Analysis of the Effect of Loss and Dispersion on Light Pulse in Fiber Optic Networks","authors":"Burak Yilmaz, A. Dolma","doi":"10.1109/SIU55565.2022.9864712","DOIUrl":"https://doi.org/10.1109/SIU55565.2022.9864712","url":null,"abstract":"Losses and dispersions, which constitute the most important transmission characteristics of the fiber, are undesirable and should be avoided in communication. In the study, the analysis of environmental and material-related losses in fiber transmission lines was made. As a result of the analysis, the causes of the losses were emphasized, the graphs of the losses in the fiber depending on the wavelength were obtained, and a study was carried out to calculate the loss amounts approximately. In the second stage of the study, dispersion and its types, which are the most important determining factors that determine the transmission speed and distance of the fiber, are briefly explained, and a simulation in single-mode fiber is prepared in order to better display the dispersion by using a computer program. In the simulation, the effect of loss and dispersion on 4 light pulses was investigated. As a result of the studies, it has been determined how the bit error rate (BER) occurs in fiber optic communication. Finally, the applications that will minimize the dispersion and loss in the fiber are emphasized.","PeriodicalId":115446,"journal":{"name":"2022 30th Signal Processing and Communications Applications Conference (SIU)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116404682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-15DOI: 10.1109/SIU55565.2022.9864902
Sertug Fdan, B. Karasulu
Different methods have been developed to optimize the Adaptive Neural Fuzzy Inference System, which is used in many fields due to its flexible structure and trainability. Within the scope of this study, three different models were produced using two different datasets, using only the first clustering method, only the second clustering method, and both the first and second clustering methods. In this study, the Fuzzy C-Mean Clustering algorithm, which is one of the most efficient methods used to reduce the number of rules in the rule base of the hybrid intelligent system is compared with the Highly Connected Subgraphs algorithm. The models were compared over the square root of the mean square error, the number of nodes, the number of fuzzy rules, and the mean training time. As a result of the study, the second clustering method formed the most efficient result in terms of error rate with 0.084 and 0,008. It has been observed that the average training time of this method is approximately 31 times longer than the first clustering method mentioned above, and approximately 52 times longer than the model in which the first and second clustering methods are used together. In this study, it has been seen that the first clustering method is more successful in reducing the rule base by optimizing the second method by determining more suitable cluster centers. Based on the experimental results obtained in our study, these two different clustering methods were compared over three different models. Discussion and scientific results are included in our study.
{"title":"Clustering Methods Comparison for Optimization of Adaptive Neural Fuzzy Inference System","authors":"Sertug Fdan, B. Karasulu","doi":"10.1109/SIU55565.2022.9864902","DOIUrl":"https://doi.org/10.1109/SIU55565.2022.9864902","url":null,"abstract":"Different methods have been developed to optimize the Adaptive Neural Fuzzy Inference System, which is used in many fields due to its flexible structure and trainability. Within the scope of this study, three different models were produced using two different datasets, using only the first clustering method, only the second clustering method, and both the first and second clustering methods. In this study, the Fuzzy C-Mean Clustering algorithm, which is one of the most efficient methods used to reduce the number of rules in the rule base of the hybrid intelligent system is compared with the Highly Connected Subgraphs algorithm. The models were compared over the square root of the mean square error, the number of nodes, the number of fuzzy rules, and the mean training time. As a result of the study, the second clustering method formed the most efficient result in terms of error rate with 0.084 and 0,008. It has been observed that the average training time of this method is approximately 31 times longer than the first clustering method mentioned above, and approximately 52 times longer than the model in which the first and second clustering methods are used together. In this study, it has been seen that the first clustering method is more successful in reducing the rule base by optimizing the second method by determining more suitable cluster centers. Based on the experimental results obtained in our study, these two different clustering methods were compared over three different models. Discussion and scientific results are included in our study.","PeriodicalId":115446,"journal":{"name":"2022 30th Signal Processing and Communications Applications Conference (SIU)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121943053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-15DOI: 10.1109/SIU55565.2022.9864894
Dizdar Ünalir, Sila Sezgin, Cansu Sena Yuva, Bengisu Yalçinkaya Gökdoğan, Elif Aydin
As Unmanned Aerial Vehicles (UAVs) have become widespread in defense industry, the radar technology that can detect them has also improved. These improvements cause UAVs to be detected more easily, which limits their effectiveness in military usage. Although the reduction of the radar cross-section (RCS) can provide a solution to this issue, the studies regarding that is insufficient in the literature. In this study, a shaping method is recommended to reduce the RCS of UAVs, and it is shown the method is effective to address the problem. Firstly, using a simulation tool, an UAV model is designed from simple shapes and the model is validated by comparing it with the ones in literature. Secondly, RCS values are measured using vertical and horizontal polarization throughout 360 degrees by incrementing the aspect angle by one degree in X-Band using the CST Studio Suite environment. Then, considering the hardware and aerodynamic requirements as well as limitations of the UAV model, a shaping technique is applied to the body, legs and the hollow parts of the UAV model with parametric simulations. The results show that the recommended shaping technique can provide a significant reduction in the RCS of an UAV.
随着无人机在国防工业中的广泛应用，探测无人机的雷达技术也在不断提高。这些改进使无人机更容易被探测到，这限制了它们在军事用途上的有效性。虽然减小雷达截面(RCS)可以解决这一问题，但文献中对此的研究不足。在本研究中，提出了一种减小无人机RCS的整形方法，并证明了该方法的有效性。首先，利用仿真工具，从简单形状出发设计无人机模型，并与文献模型进行对比验证。其次，使用CST Studio Suite环境，通过在x波段增加1度的纵横偏振度，在360度范围内测量RCS值。然后，考虑到无人机模型的硬件和气动要求，以及无人机模型的局限性，对无人机模型的机身、腿和空心部分进行了参数化仿真。结果表明，所推荐的整形技术可以显著降低无人机的RCS。
{"title":"Low Radar Cross Section UAV Design in X-Band","authors":"Dizdar Ünalir, Sila Sezgin, Cansu Sena Yuva, Bengisu Yalçinkaya Gökdoğan, Elif Aydin","doi":"10.1109/SIU55565.2022.9864894","DOIUrl":"https://doi.org/10.1109/SIU55565.2022.9864894","url":null,"abstract":"As Unmanned Aerial Vehicles (UAVs) have become widespread in defense industry, the radar technology that can detect them has also improved. These improvements cause UAVs to be detected more easily, which limits their effectiveness in military usage. Although the reduction of the radar cross-section (RCS) can provide a solution to this issue, the studies regarding that is insufficient in the literature. In this study, a shaping method is recommended to reduce the RCS of UAVs, and it is shown the method is effective to address the problem. Firstly, using a simulation tool, an UAV model is designed from simple shapes and the model is validated by comparing it with the ones in literature. Secondly, RCS values are measured using vertical and horizontal polarization throughout 360 degrees by incrementing the aspect angle by one degree in X-Band using the CST Studio Suite environment. Then, considering the hardware and aerodynamic requirements as well as limitations of the UAV model, a shaping technique is applied to the body, legs and the hollow parts of the UAV model with parametric simulations. The results show that the recommended shaping technique can provide a significant reduction in the RCS of an UAV.","PeriodicalId":115446,"journal":{"name":"2022 30th Signal Processing and Communications Applications Conference (SIU)","volume":"2 3-4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122184877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-15DOI: 10.1109/SIU55565.2022.9864667
Efe Berkay Yitim, E. G. Schmidt
This paper proposes AXI Data Shaper (ADS) which enables bandwidth allocation to the communicating modules on a shared AXI (Advanced eXtensible Interface) Interface. To this end, the first contribution of this paper is the detailed algorithmic description of ADS and its implementation on an FPGA SoC Platform. The second contribution is a comprehensive experimental study of ADS with measurements collected from the evaluation board. Our results show that ADS can provide Quality of Service to the connected modules by allocating bandwidth as configured and provide isolation and protection among the data transmissions.
本文提出了AXI Data Shaper (ADS)，它能在共享的AXI (Advanced eXtensible Interface，高级可扩展接口)接口上对通信模块进行带宽分配。为此，本文的第一个贡献是ADS的详细算法描述及其在FPGA SoC平台上的实现。第二个贡献是从评估委员会收集的测量数据对ADS进行了全面的实验研究。研究结果表明，ADS可以通过按配置分配带宽为连接模块提供服务质量，并在数据传输之间提供隔离和保护。
{"title":"An AXI Data Shaper for Heterogeneous FPGA System-on-Chip (SoC) Architectures","authors":"Efe Berkay Yitim, E. G. Schmidt","doi":"10.1109/SIU55565.2022.9864667","DOIUrl":"https://doi.org/10.1109/SIU55565.2022.9864667","url":null,"abstract":"This paper proposes AXI Data Shaper (ADS) which enables bandwidth allocation to the communicating modules on a shared AXI (Advanced eXtensible Interface) Interface. To this end, the first contribution of this paper is the detailed algorithmic description of ADS and its implementation on an FPGA SoC Platform. The second contribution is a comprehensive experimental study of ADS with measurements collected from the evaluation board. Our results show that ADS can provide Quality of Service to the connected modules by allocating bandwidth as configured and provide isolation and protection among the data transmissions.","PeriodicalId":115446,"journal":{"name":"2022 30th Signal Processing and Communications Applications Conference (SIU)","volume":"446 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125772310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-15DOI: 10.1109/SIU55565.2022.9864841
Sude Pehlivan, Burak Akbugday, A. Akan, Reza Sadighzadeh
In this study, a method is proposed to detect the presence of olfactory stimuli from Electroencephalogram (EEG) signals to be used in neuromarketing applications. Odor is used in different ways in neuromarketing applications since it stimulates various emotions. Multi-channel EEG signals were recorded from the volunteers while they were subjected to two open boxes of unscented and scented products in succession. After the necessary preprocessing steps, EEG sub-band powers were calculated for 14 EEG channels. These features were classified using machine learning methods, and the EEG segments in which the olfactory stimulus was present were classified. The results show that the proposed method gives successful results with 92% accuracy, 93% precision, 92% recall, and 92% F1-score using the Random Forest classifier.
{"title":"Detection of Olfactory Stimulus from EEG Signals for Neuromarketing Applications","authors":"Sude Pehlivan, Burak Akbugday, A. Akan, Reza Sadighzadeh","doi":"10.1109/SIU55565.2022.9864841","DOIUrl":"https://doi.org/10.1109/SIU55565.2022.9864841","url":null,"abstract":"In this study, a method is proposed to detect the presence of olfactory stimuli from Electroencephalogram (EEG) signals to be used in neuromarketing applications. Odor is used in different ways in neuromarketing applications since it stimulates various emotions. Multi-channel EEG signals were recorded from the volunteers while they were subjected to two open boxes of unscented and scented products in succession. After the necessary preprocessing steps, EEG sub-band powers were calculated for 14 EEG channels. These features were classified using machine learning methods, and the EEG segments in which the olfactory stimulus was present were classified. The results show that the proposed method gives successful results with 92% accuracy, 93% precision, 92% recall, and 92% F1-score using the Random Forest classifier.","PeriodicalId":115446,"journal":{"name":"2022 30th Signal Processing and Communications Applications Conference (SIU)","volume":"45 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125895039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-15DOI: 10.1109/SIU55565.2022.9864832
A. Çapar, Ramazan Cagac, Nurcan Komutan
Autofocusing has critical importance for imaging systems with motorized microscopes in healthcare. It is not possible to diagnose on a picture that captured out of focus. In the literature, it has been observed that there are limited studies on focusing methods specific to fluorescent microscopes. In this study, a focus metric is proposed special to fluorescent microscope images. The proposed metric evaluates the responses generated by gradient filters of varying kernel size at a pixel point, and takes into account their standard deviations. The proposed method was tested on lung and breast tissue samples obtained with fluorescent microscope, and experimental results were reported. It is shown that the developed method overperforms the local gradient filters and produces an average error of 0.16 levels.
{"title":"A Statistical Focusing Metric for Fluorescent Microscopy","authors":"A. Çapar, Ramazan Cagac, Nurcan Komutan","doi":"10.1109/SIU55565.2022.9864832","DOIUrl":"https://doi.org/10.1109/SIU55565.2022.9864832","url":null,"abstract":"Autofocusing has critical importance for imaging systems with motorized microscopes in healthcare. It is not possible to diagnose on a picture that captured out of focus. In the literature, it has been observed that there are limited studies on focusing methods specific to fluorescent microscopes. In this study, a focus metric is proposed special to fluorescent microscope images. The proposed metric evaluates the responses generated by gradient filters of varying kernel size at a pixel point, and takes into account their standard deviations. The proposed method was tested on lung and breast tissue samples obtained with fluorescent microscope, and experimental results were reported. It is shown that the developed method overperforms the local gradient filters and produces an average error of 0.16 levels.","PeriodicalId":115446,"journal":{"name":"2022 30th Signal Processing and Communications Applications Conference (SIU)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129321412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-15DOI: 10.1109/SIU55565.2022.9864920
Ahmet R. Emirdagi, Fadime Tokmak, Nursena Köprücü, Kardelen Akar, A. Vural, E. Erzin
Stride time and stance phase ratio are supportive biomarkers used in the diagnosis and treatment of gait disorders and are currently frequently used in research studies. In this study, the 3-axis accelerometer signal, taken from the foot, was denoised by a low-pass FIR (finite impulse response) filter. By using the fundamental frequency analysis the dominant frequency was found and with that frequency an optimal length for a window to be shifted across the whole signal for further purposes. And the turning region was extracted by using the Pearson correlation coefficient with the segments that overlapped by shifting the selected window over the whole signal, after getting the walking segments the stride time parameter is calculated by using a simple peak-picking algorithm. The stance and swing periods of the pseudo-steps, which emerged as a result of the double step time calculation algorithm, were found with the dynamic time warping method, and the ratio of the stance phase in a step to the whole step was calculated as a percentage. The results found were compared with the results of the APDM system, and the mean absolute error rate was calculated as 0.029 s for the stride time and 0.0084 for the stance phase ratio.
{"title":"Detection of Stride Time and Stance Phase Ratio from Accelerometer Data for Gait Analysis","authors":"Ahmet R. Emirdagi, Fadime Tokmak, Nursena Köprücü, Kardelen Akar, A. Vural, E. Erzin","doi":"10.1109/SIU55565.2022.9864920","DOIUrl":"https://doi.org/10.1109/SIU55565.2022.9864920","url":null,"abstract":"Stride time and stance phase ratio are supportive biomarkers used in the diagnosis and treatment of gait disorders and are currently frequently used in research studies. In this study, the 3-axis accelerometer signal, taken from the foot, was denoised by a low-pass FIR (finite impulse response) filter. By using the fundamental frequency analysis the dominant frequency was found and with that frequency an optimal length for a window to be shifted across the whole signal for further purposes. And the turning region was extracted by using the Pearson correlation coefficient with the segments that overlapped by shifting the selected window over the whole signal, after getting the walking segments the stride time parameter is calculated by using a simple peak-picking algorithm. The stance and swing periods of the pseudo-steps, which emerged as a result of the double step time calculation algorithm, were found with the dynamic time warping method, and the ratio of the stance phase in a step to the whole step was calculated as a percentage. The results found were compared with the results of the APDM system, and the mean absolute error rate was calculated as 0.029 s for the stride time and 0.0084 for the stance phase ratio.","PeriodicalId":115446,"journal":{"name":"2022 30th Signal Processing and Communications Applications Conference (SIU)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127028833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-15DOI: 10.1109/SIU55565.2022.9864858
ilkay Ulusoy, Botan Yildirim
A new method for extracting clean samples from noisy labelled classification dataset without using any clean dataset and making any assumption related to noise rate is proposed in this work. The proposed method suggests creating artificial samples, which are mimicking noisy samples and absolutely noisy, to understand behavior of noisy samples during training of a classifier neural network. The proposed method investigates behavior of artificial samples during training to classify other samples as clean or noisy. Performance of clean sample extraction and classifier neural network trained with the extracted clean samples are observed with using proposed method. When presented results are observed, it is proved that the proposed algorithm is sucessful in terms of extracting clean dataset and provides better or similar results with compared algorithms.
{"title":"Filtering Clean Sample from Noisy Datasets by Creating and Analyzing Artifical Class","authors":"ilkay Ulusoy, Botan Yildirim","doi":"10.1109/SIU55565.2022.9864858","DOIUrl":"https://doi.org/10.1109/SIU55565.2022.9864858","url":null,"abstract":"A new method for extracting clean samples from noisy labelled classification dataset without using any clean dataset and making any assumption related to noise rate is proposed in this work. The proposed method suggests creating artificial samples, which are mimicking noisy samples and absolutely noisy, to understand behavior of noisy samples during training of a classifier neural network. The proposed method investigates behavior of artificial samples during training to classify other samples as clean or noisy. Performance of clean sample extraction and classifier neural network trained with the extracted clean samples are observed with using proposed method. When presented results are observed, it is proved that the proposed algorithm is sucessful in terms of extracting clean dataset and provides better or similar results with compared algorithms.","PeriodicalId":115446,"journal":{"name":"2022 30th Signal Processing and Communications Applications Conference (SIU)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128972187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-15DOI: 10.1109/SIU55565.2022.9864740
Talat Kepezkaya, A. Özen
In this study, it is proposed to combine fast Walsh Hadamard transform (FWHT) with orthogonal transforms such as discrete cosine transform (DCT) and discrete sine transform (DST) to increase the performance of time domain (TDE) and frequency domain channel equalizers (FDE) used in OFDM systems. In order to test the performance of the proposed FWHT FFT/DCT/DST-OFDM waveforms with TDE and FDE, numerical simulation studies are carried out in the frequency selective Rayleigh fading channel environment. From the obtained numerical results, it is understood that the proposed FWHT FFT/DCT/DST OFDM-TDE systems have approximately 8 dB better bit error rate (BER) performance than FWHT FFT/DCT/DST OFDM-FDE methods.
{"title":"Analysis of the Effects of Orthogonal Transformation Techniques on Channel Equalizers Used in OFDM","authors":"Talat Kepezkaya, A. Özen","doi":"10.1109/SIU55565.2022.9864740","DOIUrl":"https://doi.org/10.1109/SIU55565.2022.9864740","url":null,"abstract":"In this study, it is proposed to combine fast Walsh Hadamard transform (FWHT) with orthogonal transforms such as discrete cosine transform (DCT) and discrete sine transform (DST) to increase the performance of time domain (TDE) and frequency domain channel equalizers (FDE) used in OFDM systems. In order to test the performance of the proposed FWHT FFT/DCT/DST-OFDM waveforms with TDE and FDE, numerical simulation studies are carried out in the frequency selective Rayleigh fading channel environment. From the obtained numerical results, it is understood that the proposed FWHT FFT/DCT/DST OFDM-TDE systems have approximately 8 dB better bit error rate (BER) performance than FWHT FFT/DCT/DST OFDM-FDE methods.","PeriodicalId":115446,"journal":{"name":"2022 30th Signal Processing and Communications Applications Conference (SIU)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131077660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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