2-D two-fold symmetric circular shaped filter design with homomorphic processing application

A design method of a linear-phased, two-dimensional (2-D), two-fold symmetric circular shaped filter is presented in this paper. Although the proposed method designs a non-separable filter, its implementation has linear complexity. The shape of the passband and the stopband is expressed in terms of level sets of second order trigonometric polynomials. This enables the transformation of the filter specifications to a Semi-Definite Program (SDP) of moderate dimension. The proposed filter outperforms currently available filter design methods. We present a performance comparison, as well as a homomorphic processing image enhancement example to illustrate the effectiveness of this method. ©2010 IEEE

Two-hop power-relaying for linear wireless sensor networks

© 2016 IEEE. This paper presents two-hop relay gain-scheduling control in a Wireless Sensor Network to estimate a static target prior characterized by Gaussian probability distribution. The target is observed by a network of linear sensors, whose observations are transmitted to a fusion center for carrying out final estimation via a amplify-And-forward relay node. We are concerned with the joint transmission power allocation for sensors and relay to optimize the minimum mean square error (MMSE) estimator, which is deployed at the fusion center. Particularly, such highly nonlinear optimization problems are solved by an iterative procedure of very low computational complexity. Simulations are provided to support the efficiency of our proposed power allocation

Subject-independent P300 BCI using ensemble classifier, dynamic stopping and adaptive learning

© 2017 IEEE. Brain-computer interfaces (BCIs) are used to assist people, especially those with verbal or physical disabilities, communicate with the computer to indicate their selections, control a device or answer questions only by their mere thoughts. Due to the noisy nature of brain signals, the required time for each experimental session must be lengthened to reach satisfactory accuracy. This is the trade-off between the speed and the precision of a BCI system. In this paper, we propose a unified method which is the integration of ensemble classifier, dynamic stopping, and adaptive learning. We are able to both increase the accuracy, as well as to reduce the spelling time of the P300-Speller. Another merit of our study is that it does not require the training phase for any new subject, hence eliminates the extensively time-consuming process for learning purposes. Experimental results show that we achieve the averaged bit rate boost up of 182% on 15 subjects. Our best achieved accuracy is 95.95% by using 7.49 flashing iterations and our best achieved bit rate is 40.87 bits/min with 83.99% accuracy and 3.64 iterations. To the best of our knowledge, these results outperformed most of the related P300-based BCI studies

Subject-Independent ERP-Based Brain-Computer Interfaces

© 2001-2011 IEEE. Brain-computer interfaces (BCIs) are desirable for people to express their thoughts, especially those with profound disabilities in communication. The classification of brain patterns for each different subject requires an extensively time-consuming learning stage specific to that person, in order to reach satisfactory accuracy performance. The training session could also be infeasible for disabled patients as they may not fully understand the training instructions. In this paper, we propose a unified classification scheme based on ensemble classifier, dynamic stopping, and adaptive learning. We apply this scheme on the P300-based BCI, with the subject-independent manner, where no learning session is required for new experimental users. According to our theoretical analysis and empirical results, the harmonized integration of these three methods can significantly boost up the average accuracy from 75.00% to 91.26%, while at the same time reduce the average spelling time from 12.62 to 6.78 iterations, approximately to two-fold faster. The experiments were conducted on a large public dataset which had been used in other related studies. Direct comparisons between our work with the others' are also reported in details

Examining responsiveness of India’s trade flows to exchange rate movements

Determinants of trade flows have always attracted researchers. In this paper, we model monthly trade flows in India over January 2000 – December 2007 in a bid to gauge their responsiveness to exchange rate movements. Capital account and overall BOP surplus have led the Indian Rupee (INR) to appreciate and forex reserves to accumulate. In so far as the RBI intervenes to stem this forex accretion by the net purchase of USD, it puts further pressure on the INR to appreciate. It therefore becomes important to study the response of the current account to these changes in the exchange rate. We employ standard empirical estimations of India’s export supply and import demand functions using data from the Reserve Bank of India. We also assess the short-term dynamics of these trade flows through error correction models. Finally, we estimate vector auto regression models to gauge the extent of contemporaneous interaction between trade flows and the explanatory variables in the system

Prevalence of thyroid disorders and thyroid autoantibodies among coastal communities of Malaysia (part of nationwide study of thyroid disorders in Malaysia)

Objectives To determine the prevalence of thyroid disorders and thyroid autoantibodies in the coastal communities of Malaysia. This study is part of a nationwide study looking into the prevalence of thyroid disorders. Methods A cross sectional study was performed in two coastal districts of rural Selangor. A village from each district was chosen where a participant from each household from the village was selected using KISH tables. Sociodemographic data, medical history, anthropometric measurement and thyroid examination were performed. The presence of goiter was recorded according to the World Health Organization (WHO) goiter grading system. Blood withdrawn was tested for thyroid function and thyroid autoantibodies. Thyroid antibodies analyses were done using Immulite 2000 system. Lowest detectable limit for anti-thyroperoxidase (antiTPO) and antithyroglobulin (antiTG) are 10 IU/mL and 20 IU/mL respectively. Low, moderate and high titre is defined 40 - 100 IU/mL, 101-1000 IU/mL and >1000 IU/mL respectively. Results A total of 418 subjects were recruited with a mean age of 54.1 ± 14.2 years. Majority were Malays (86.8%), followed by Indians (11.7%) and Chinese (1.4%). Among respondents, 2.9% had Grade 1 and 8.9% had Grade 2 goitre. A mere 3.4% had clinically palpable thyroid nodules. A total of 411 blood samples were available for thyroid level assessment, with 1.9% of respondents were found to have hypothyroidism while 85.6% had TSH in the range of 0.32-2.5 mIU/L. The prevalence of overt and subclinical hypothyroidism was 0.2% and 1.7% AFES 2015 10 – 13 December 2015 respectively. On the otherhand, 3.4% of respondents were hyperthyroid (TSH < 0.32 mIU/L) with prevalence of overt and subclinical hyperthyroidism being 0.5% and 2.9% respectively. Among 417 samples which were available for antiTPO analysis, 8.9% has detectable antiTPO titre (>40.0 IU/mL), with 4.3% had moderate and 2.4% had high antiTPO titres. One respondent (10%) from among those with high antiTPO titres was found to have T3 thyrotoxicosis. Fourty percent of euthyroid respondents with high titre and 38.9% with moderate titre had high normal TSH, in the range of 2.51 – 5.00 mIU/L (p<0.001). Among 417 samples which are available for antiTG analysis, 3.4% and 5.3% had low detectable and moderate antiTG titres respectively. Only 0.5% (2 respondents) had high antiTG titre (>1000 IU/mL) and found to be hypothyroid. Among those with moderately positive titre, 9.1% were hyperthyroid and majority (63.6%), although euthyroid, had TSH levels between 0.32 – 2.50 mIU/L (p<0.001). Conclusion The low prevalence of thyroid antibodies and thyroid disorders in coastal communities could be attributed to the iodine sufficient status in those areas. Euthyroid respondents with moderate and high antiTPO titres tend to have higher TSH levels, while those with moderate and high antiTG titres had lower TSH levels

Joint optimization of source power allocation and cooperative beamforming for SC-FDMA multi-user multi-relay networks

© 2013 IEEE. This paper is concerned with design problems of joint source power allocation and relay beamforming in multiuser multi-relay networks that use single-carrier frequency division multiple access (SC-FDMA) and amplify-and-forward relaying. Examined are the joint programs of (i) maximizing the minimum signal-to-interference-plus-noise ratio (SINR) under various transmitted power constraints, and (ii) minimizing the total transmitted power subject to prescribed SINR thresholds of users. Although these optimization problems are highly nonconvex and have large dimensions, by exploiting their partial convexities and making elegant nonlinear variable changes, they are recast as d.c. (difference of two convex) programs. Efficient d.c. iterative procedures are then developed to find the solutions. Simplified joint programs under the two cases of equal source power and equal relay beamforming weights, respectively, are also considered. Branch-and-bound algorithms of deterministic global optimization are then proposed for solving the simplified joint programs. Simulation results confirm the excellent performance and computational efficiency of all the proposed solutions

Fast local D.C. programming for optimal power allocation in wireless networks

Power allocations in an interference-limited wireless network for global maximization of the weighted sum throughput or global maximization of the minimum rate among network links are not only important but also very hard optimization problems due to their nonconvexity nature. Recently developed methods are either unable to locate the global optimal solutions or prohibitively complex for practical applications. This paper exploits the d.c. (difference of two convex functions/sets) structure of either the objective function or constraint of the these global optimization problems to develop efficient iterative algorithms with very low complexity. Numerical results demonstrate that the developed algorithms are able to locate the global optimal solutions by only a few iterations and they are superior to the previously-proposed methods in both performance and computation complexity. © 2011 IEEE

Error-entropy based channel state estimation of spatially correlated MIMO-OFDM

This paper deals with optimized training sequences to estimate multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) channel states in the presence of spatial fading correlations. The optimization criterion is the entropy minimization of the error between the high multi-dimensional and correlated channel state and its estimator. The globally optimized training sequences are exactly solved by a semi-definite programming (SDP) of tractable computational complexity O((Mt(Mt + 1)/2)2.5), where Mt is the transmit antenna number. With new tight two-sided bounds for the objective function, the optimal value of the generic SDP can be approximately solved by the standard water-filling algorithm. Intensive simulation results are provided to illustrate the performance of our methods. © 2011 IEEE