Modified Alternative-signal Technique for Sequential Optimisation for PAPR Reduction in OFDM-OQAM Systems

A modified alternative signal technique for reducing peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing systems employing offset quadrature amplitude modulation (OFDM-OQAM) is proposed. Lower PAPR reduces the complexity of digital to analog converters and results in increasing the efficiency of power amplifiers. The main objective of the algorithm is to decrease PAPR with low complexity. The alternative signal method involves the individual alternative signal (AS-I) and combined alternative signal (AS-C) algorithms. Both the algorithms decrease the peak to average power ratio of OFDM-OQAM signals and AS-C algorithm performs better in decreasing PAPR. However the complexity of AS-C algorithm is very high compared to that of AS-I. To achieve reduction in PAPR with low complexity, modified alternative signal technique with sequential optimisation (MAS-S) is proposed. The quantitative PAPR analysis and complexity analysis of the proposed algorithm are carried out. It is demonstrated that MAS-S algorithm simultaneously achieves PAPR reduction and low complexity

Performance Analysis of MIMO SFBC CI-COFDM System against the Nonlinear Distortion and Narrowband Interference

Carrier Interferometry Coded Orthogonal Frequency Division Multiplexing (CI-COFDM) system has been widely studied in multi-carrier communication system. The CI-COFDM system spreads each coded information symbol across all N sub-carriers using orthogonal CI spreading codes. The CI-COFDM system shows the advantages of Peak to Average Power Ratio (PAPR) reduction, frequency diversity and coding gain without any loss of communication throughput. On the other side, a great attention has been devoted to Multi Input Multi Output (MIMO) antenna systems and space-time-frequency processing. In this paper, we focus on two Transmit (Tx)/one Receive (Rx) antennas configuration and evaluate the performance of MIMO OFDM, MIMO CIOFDM and MIMO CI-COFDM systems. Space Frequency Block Coding (SFBC) is applied to MIMO OFDM, MIMO CI-ODFM and MIMO CI-COFDM systems. For CI-COFDM realization, digital implemented CI-COFDM is used in which information conventional is encoded, CI code spreading operation and carrier allocation are processed by IFFT type operation. From simulation results, it is shown that MIMO SFBC CI-COFDM reduces PAPR significantly as compared with that of MIMO SFBC CI-OFDM and MIMO SFBC OFDM systems. In Narrow Band Interference (NBI) channel MIMO SFBC CI-COFDM systems achieve considerable Bit Error Rate (BER) improvement compared with MMO SFBC CI-OFDM and MIMO SFBC OFDM system

iEEG based Epileptic Seizure Detection using Reconstruction Independent Component Analysis and Long Short Term Memory Network

In recent decades, an epileptic seizure is a neurological disorder, which is commonly detected from intracranial Electroencephalogram (iEEG) signals. However, the visual interpretation and inspection of iEEG signal is subjective variability, a time-consuming mechanism, slow and vulnerable to errors. In this research article, an automated epileptic seizure detection model is proposed to highlight the above-mentioned concerns. The proposed automated model integrates the Reconstruction Independent Component Analysis (RICA) and Long Short Term Memory (LSTM) for seizure detection. In the proposed model, RICA is utilized to extract the features from the normalized iEEG signals, and then the obtained feature vectors are fed to the LSTM network for classification, which effectively classifies inter-ictal and ictal iEEG signals. This experimental outcome showed that the proposed RICA-LSTM model achieved an accuracy of 98.92%, sensitivity of 99.01%, specificity of 98.68%, balanced accuracy of 99.24%, and f-score of 98.25% in epileptic seizure recognition on the SWEC-ETHZ iEEG database, which is better compared to the conventional machine learning classifiers

Performance Degradation in Pre-rake Frequency-division Duplex/ Direct Sequence-code Division Multiple Access Systems

The transmitter-based pre-rake diversity combining technique reduces the complexity, size and cost of the mobile unit (MU), while achieving the same inter symbol interference (ISI) mitigation effects of rake receiver for direct sequence-code division multiple access (DS-CDMA) systems. The technique is based on preprocessing of transmitted signal relying on knowledge of the channel state information (CSI) before transmission. In most of the previous works, this a priori information is either assumed or estimated for the uplink and the same is applied to the downlink in time division duplex (TDD) systems due to channel reciprocity. In this paper, a method for channel prediction to evaluate the pre-rake system using binary phaseshift keying (BPSK) modulation in frequency-division duplex (FDD) through analytical and computer simulations for DS-CDMA downlink has been proposed. The performance of the system was also evaluated under ideal and predicted channel conditions using different spreading codes. The findings will have widespread applications in defence communication equipment.Defence Science Journal, 2010, 60(3), pp.282-289, DOI:http://dx.doi.org/10.14429/dsj.60.35

Optimized DWT Based Digital Image Watermarking and Extraction Using RNN-LSTM

The rapid growth of Internet and the fast emergence of multi-media applications over the past decades have led to new problems such as illegal copying, digital plagiarism, distribution and use of copyrighted digital data. Watermarking digital data for copyright protection is a current need of the community. For embedding watermarks, robust algorithms in die media will resolve copyright infringements. Therefore, to enhance the robustness, optimization techniques and deep neural network concepts are utilized. In this paper, the optimized Discrete Wavelet Transform (DWT) is utilized for embedding the watermark. The optimization algorithm is a combination of Simulated Annealing (SA) and Tunicate Swarm Algorithm (TSA). After performing the embedding process, the extraction is processed by deep neural network concept of Recurrent Neural Network based Long Short-Term Memory (RNN-LSTM). From the extraction process, the original image is obtained by this RNN-LSTM method. The experimental set up is carried out in the MATLAB platform. The performance metrics of PSNR, NC and SSIM are determined and compared with existing optimization and machine learning approaches. The results are achieved under various attacks to show the robustness of the proposed work

Vectored Machine Learning Rearing Process: Early Detection of Leaf Diseases

619-625Over the past years, the plant leaf analyses through image processing have drawn a remarkable approach in assessing leaf disease severity through accurate and precise conclusions. We proposed, ‘Scale Invariant Feature Transform’ (SIFT) based Distinctive Scale Invariant Mapping Procedure (DSIMP) for training images. Random Separation Propagation (RSP) Procedure and Redundant multiclass Support Vector Machine (RM-SVM) are implemented to detect the rice and groundnut leaf diseases at its early stages. Discriminative Gray Level Co-occurrence Matrix (DGLCM) and K means clustering is used for recognition and quantification to give the best color analysis. Experiments with 1000 samples of rice and groundnut leaf images show promising performance

Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease

Background: Experimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. Methods: We conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. RESULTS: At 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in the 300-mg group than in the placebo group. Canakinumab did not reduce lipid levels from baseline. At a median follow-up of 3.7 years, the incidence rate for the primary end point was 4.50 events per 100 person-years in the placebo group, 4.11 events per 100 person-years in the 50-mg group, 3.86 events per 100 person-years in the 150-mg group, and 3.90 events per 100 person-years in the 300-mg group. The hazard ratios as compared with placebo were as follows: in the 50-mg group, 0.93 (95% confidence interval [CI], 0.80 to 1.07; P = 0.30); in the 150-mg group, 0.85 (95% CI, 0.74 to 0.98; P = 0.021); and in the 300-mg group, 0.86 (95% CI, 0.75 to 0.99; P = 0.031). The 150-mg dose, but not the other doses, met the prespecified multiplicity-adjusted threshold for statistical significance for the primary end point and the secondary end point that additionally included hospitalization for unstable angina that led to urgent revascularization (hazard ratio vs. placebo, 0.83; 95% CI, 0.73 to 0.95; P = 0.005). Canakinumab was associated with a higher incidence of fatal infection than was placebo. There was no significant difference in all-cause mortality (hazard ratio for all canakinumab doses vs. placebo, 0.94; 95% CI, 0.83 to 1.06; P = 0.31). Conclusions: Antiinflammatory therapy targeting the interleukin-1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid-level lowering. (Funded by Novartis; CANTOS ClinicalTrials.gov number, NCT01327846.

An assessment of the physiological reactions of sows to their environment in Manawatu, New Zealand : being a thesis presented in partial fulfilment of the requirements for the Degree of Master of Agricultural Science

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A novel reduced complexity optimized PTS technique for PAPR reduction in wireless OFDM systems

In this paper, we propose a novel low complexity Partial Transmit Sequence (PTS) technique employing Random phase sequence matrix (RPSM) for peak to average power ratio (PAPR) reduction in orthogonal frequency division multiplexing (OFDM) systems. The main goal of our suggested scheme is to achieve the optimum phase sequence matrix to minimize PAPR and simultaneously reduce the computational complexity by decreasing the number of Inverse Fast Fourier Transform (IFFT) operations required. Lower PAPR reduces the complexity of Digital to Analog converters (DAC) and increases the efficiency of power amplifiers. Analytical expressions for Complementary Cumulative Distribution Function (CCDF), Number of subcarriers, subblocks and Total computational complexity are derived. Simulation results match closely with the analytical results. It is demonstrated that a favorable tradeoff can be achieved between the reduction of PAPR and computational complexity. It is observed that the suggested modified PTS technique outperforms the traditional PTS (T-PTS) technique

Audio streaming over low data rate wireless system

Audio applications over wireless networks have recently emerged as a promising research field. However, the limits in terms of communication bandwidth and transmission power have withstood the design of low-power embedded nodes for audio communication. In this work we describe the implementation details of an embedded system for the wireless broadcasting of audio signals over the low data rate wireless system. Here the audio data transferred through a wireless network instead of alarms. That is it tells how to go and where the disaster occurs. This is a challenging task because the effective data rate available in mesh network is low. Most of the bandwidth is consumed by alarm/data communication and audio steering is a real time application. Because of this low data rate we use Huffman compression and decompression algorithms to compress and decompress the audio data