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Suganthi, M.
- Joint Symbol Timing Estimation and Carrier Phase Synchronization for OFDM based WLAN Systems
Abstract Views :201 |
PDF Views:4
Authors
Affiliations
1 Mepco Schlenk Engineering College, Sivakasi - 626 005, IN
2 Thiagarajar College of Engineering, Madurai – 626 015, IN
1 Mepco Schlenk Engineering College, Sivakasi - 626 005, IN
2 Thiagarajar College of Engineering, Madurai – 626 015, IN
Source
Wireless Communication, Vol 1, No 3 (2009), Pagination: 136-141Abstract
In this paper, a joint symbol timing estimation and carrier phase synchronization method for Orthogonal Frequency Division Multiplexing (OFDM) system is implemented for a Wireless Local Area Network (WLAN). Earlier approaches for symbol timing estimation make use of correlation of samples within the preamble. So preamble should be chosen with good autocorrelation property. Thus estimation method directly depends on the preamble. The implemented method for timing estimation in this paper is preamble independent. This method can be applied for any preamble structure and this scheme gives more accurate estimate of symbol timing. Also a method for carrier phase recovery is implemented in OFDM WLAN system. This algorithm for carrier phase compensation can effectively recover Residual Frequency Offset (RFO) and phase in the presence of Inter Carrier Interference (ICI). This scheme for symbol timing and carrier phase recovery is analyzed for WLAN environment and simulation results are shown.
Keywords
Carrier Frequency Offset (CFO), Correlation Sequence of Preamble (CSP), Decision-Directed (DD), Inter Carrier Interference (ICI), Orthogonal Frequency Division Multiplexing (OFDM), Quadrant Decision (QD), Residual Frequency Offset (RFO).
- Neural Networks Based QoS Scheduling in WiMAX
Abstract Views :191 |
PDF Views:2
Authors
Affiliations
1 ECE Department, at SRCE, Alangulam, Tirunelveli, IN
2 Bharathiar Institute of Engg. For women, Attur, Chinna Salem, IN
3 IIT, Delhi, IN
4 ECE Dept. at TCE, Madurai, IN
1 ECE Department, at SRCE, Alangulam, Tirunelveli, IN
2 Bharathiar Institute of Engg. For women, Attur, Chinna Salem, IN
3 IIT, Delhi, IN
4 ECE Dept. at TCE, Madurai, IN
Source
Networking and Communication Engineering, Vol 3, No 1 (2011), Pagination: 73-78Abstract
Wireless Interoperability for Microwave Access (WiMAX) is one of the most familiar broadband wireless access technologies that support multimedia transmission. IEEE802.16 Medium Access Control (MAC) covers a large area for bandwidth allocation and QoS mechanisms for various types of applications. Nevertheless, the standard lacks a MAC scheduling algorithm that has a multi-dimensional objective of satisfying QoS requirements of the users, maximizing channel utilization while ensuring fairness among users. So we are proposing a novel Priority based Scheduling Algorithm using Fuzzy logic and Artificial neural networks (ANN) that addresses these aspects simultaneously. The initial results show that a fair amount of fairness is attained while keeping the priority intact. Results also show that maximum channel utilization is achieved with a negligible increment in processing time.Keywords
Artificial Neural Networks, Fuzzy Logic, Fairness, QoS, Scheduling Algorithms.- An Efficient Pose & Illumination Normalization Preprocessing Technique for Face Recognition
Abstract Views :228 |
PDF Views:5
Authors
Affiliations
1 Mahendra Engineering College, Mallasamudram, Namakkal, IN
2 Kumaraguru College of Technology, Coimbatore, IN
1 Mahendra Engineering College, Mallasamudram, Namakkal, IN
2 Kumaraguru College of Technology, Coimbatore, IN
Source
Digital Image Processing, Vol 6, No 6 (2014), Pagination: 254-260Abstract
Face recognition has made significant improvement in the last decade, but robust commercial applications are still lacking. Current authentication/ identification applications are limited to controlled settings, e.g., limited pose and illumination changes. This paper proposes a novel framework for real-world face recognition in uncontrolled settings named Face Analysis for Commercial Entities (FACE). Its robustness comes from normalization (“correction”) strategies to address pose and illumination variations. FACE adopts reliability indices, which estimate the “acceptability” of the final identification decision made by the classifier. The rewards of FACE are: data fusion; online identity management; and interoperability. The results obtained by FACE witness a significant increase in accuracy when compared with the results produced by the other algorithmic rule considered.
Keywords
Face Recognition, Identity Management, Inter Operability, Pose and Illumination Changes, Reliability Indices.- BER Performance Comparison of Multiple Antenna Using Space Time Block Coded OFDM System in Multipath Fading Environment
Abstract Views :220 |
PDF Views:0
Authors
Affiliations
1 Department of Electronics and Communication Engineering, Kamaraj College of Engineering and Technology, Tamil Nadu, IN
2 Department of Electronics and Communication Engineering, Thiagarajar College of Engineering, Tamil Nadu, IN
3 Department of Electronics and Communication Engineering, P.S.R.R.College of Engineering for Women, Tamil Nadu, IN
1 Department of Electronics and Communication Engineering, Kamaraj College of Engineering and Technology, Tamil Nadu, IN
2 Department of Electronics and Communication Engineering, Thiagarajar College of Engineering, Tamil Nadu, IN
3 Department of Electronics and Communication Engineering, P.S.R.R.College of Engineering for Women, Tamil Nadu, IN
Source
ICTACT Journal on Communication Technology, Vol 2, No 1 (2011), Pagination: 277-282Abstract
Present wireless communication systems uses FDMA, TDMA and CDMA techniques and are facing various issues like multipath fading, time dispersion which leads to inter symbol interference (ISI), lower bit rate capacity and less spectral efficiency. In a conventional terrestrial broadcasting, the transmitted signal arrives at the receiver through various paths of different lengths. Hence multiple versions of the signal interfere with each other and it becomes difficult to extract the original information. The use of Space Time Block Coded (STBC) Orthogonal Frequency Division Multiplexing (OFDM) technique provides better solution for the above issues. In this paper, we study the Bit Error Rate (BER) performance of STBC OFDM system employing BPSK, QPSK and QAM modulations. As STBCs have been derived from Generalized Complex Orthogonal Designs (GCOD), the norms of the column vectors are the same (e.g., Alamouti Code). We present an analysis of how multiple transmitting antennas and one receiving antenna produces reduced BER at lower value of SNR. From the simulation results, we observed that the BPSK allows improved BER performance over a noisy channel at the cost of maximum data transmission capacity. But the use of QPSK and QAM allows higher transmission capacity at the cost of slight increase in the probability of error.Keywords
Generalized Complex Orthogonal Design, Space Time Block Code, Alamouti Code, OFDM, Antenna Diversity.- Prediction of Seed Purity and Variety Identification Using Image Mining Techniques
Abstract Views :110 |
PDF Views:2
Authors
Affiliations
1 Department of Computer Science, Bishop Heber College, IN
1 Department of Computer Science, Bishop Heber College, IN
Source
ICTACT Journal on Soft Computing, Vol 12, No 4 (2022), Pagination: 2715-2722Abstract
Seed is a little embryonic plant that can be used to introduce plant infections to new areas while also allowing them to survive from one cropping season to the next. Seed health is a well-known component in modern agricultural science for achieving the required plant population and yield. Seed-borne fungus are a major biotic constraint in seed production around the world. The detection of seed-borne pathogens by seed health testing is a crucial step in the treatment of crop diseases. Speed and accuracy are critical requirements for long-term economic growth, competitiveness, and sustainability in agricultural output. Because human judgements in identifying objects and situations are variable, subjective, and delayed, seed prediction activities are costly and unreliable. Machine vision technology provides a nondestructive, cost-effective, quick, and accurate option for automated procedures. Seed variety, seed type (country seed or hybrid seed), seed health, and purity prediction were the four basic processes. We began the first procedure by aligning the seed bodies in the same direction using a seed orientation approach. Then, to detect atypical physical seed samples, a quality screening procedure was used. Their physical characteristics, such as shape, colour, and texture, were retrieved to serve as data representations for the prediction. This research introduces a new fuzzy cognitive map (FCM) model based on deep learning neural networks that predicts seed purity tests using data from biological investigations. The relevant data features from the seed test are extracted by FCM, which then effectively initialises the deep neural networks. The Levenberg–Marquardt (LM) technique for deep neural networks was discovered to improve seed purity test prediction. Four statistical machine learning algorithms (BP-ANN, Multivariate regression, and FCMLM deep learning). Furthermore, we demonstrated an improvement in the system's overall performance in terms of data quality, including seed orientation and quality screening. In independent numerical testing, the correlation coefficient between predicted values and true values acquired from experiments reached 0.9.Keywords
Fuzzy Cognitive Map, Deep Learning, FCMLM Deep Learning, BP-ANN, Multivariate Regression, Seed PurityReferences
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