A New State-Regularized QRRLS Algorithm with Variable Forgetting Factor

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A new transform-domain regularized recursive least M-estimate algorithm for a robust linear estimation

This brief proposes a new transform-domain (TD) regularized M-estimation (TD-R-ME) algorithm for a robust linear estimation in an impulsive noise environment and develops an efficient QR-decomposition-based algorithm for recursive implementation. By formulating the robust regularized linear estimation in transformed regression coefficients, the proposed TD-R-ME algorithm was found to offer better estimation accuracy than direct application of regularization techniques to estimate system coefficients when they are correlated. Furthermore, a QR-based algorithm and an effective adaptive method for selecting regularization parameters are developed for recursive implementation of the TD-R-ME algorithm. Simulation results show that the proposed TD regularized QR recursive least M-estimate (TD-R-QRRLM) algorithm offers improved performance over its least squares counterpart in an impulsive noise environment. Moreover, a TD smoothly clipped absolute deviation R-QRRLM was found to give a better steady-state excess mean square error than other QRRLM-related methods when regression coefficients are correlated. © 2006 IEEE.published_or_final_versio

A new regularized transform-domain NLMS adaptive filtering algorithm

The transform domain normalized LMS (TD-NLMS)-adaptive filtering algorithm is an efficient adaptive filter with fast convergence speed and reasonably low arithmetic complexity. However, it is sensitive to the level of the excitation signal, which may vary significantly over time in speech and audio signals. This paper proposes a new regularized transform domain NLMS (R-TDNLMS) algorithm and studies its mean and mean square convergence performance. The proposed algorithm extends the conventional TDNLMS algorithm by imposing a regularization term on the coefficients to reduce the variance of the estimator. The mean and mean square convergence behaviors of the proposed algorithm are studied to characterize its convergence condition and steady-state excess mean squares error (MSE). It shows that regularization can help to reduce the MSE for coloured inputs by trading slight bias for variance. Moreover, the immunity to varying input signal level is significantly reduced. Computer simulations are conducted to examine the effectiveness of the proposed algorithm and they are in good agreement with the theoretical analysis. © 2010 IEEE.published_or_final_versionThe 2010 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS 2010), Kuala Lumpur, Malaysia, 6-9 December 2010. In Proceedings of APCCAS, 2010, p. 696-69

A new regularized QRD recursive least M-estimate algorithm: Performance analysis and applications

Proceedings of the International Conference on Green Circuits and Systems, 2010, p. 190-195This paper proposes a new regularized QR decomposition based recursive least M-estimate (R-QRRLM) adaptive filtering algorithm and studies its mean and mean square convergence performance and application to acoustic echo cancellation (AEC). The proposed algorithm extends the conventional RLM algorithm by imposing a weighted L2 regularization term on the coefficients to reduce the variance of the estimator. Moreover, a QRD-based algorithm is employed for efficient recursive implementation and improved numerical property. The mean convergence analysis shows that a bias solution to the classical Wiener solution will be introduced due to the regularization. The steady-state excess mean square error (EMSE) is derived and it suggests that the variance will decrease while the bias will increase with the regularization parameter. Therefore, regularization can help to trade bias for variance. In this study, the regularization parameter can be adaptively selected and the resultant variable regularization parameter QRRLM (VR-QRRLM) algorithm can obtain both high immunity to input variation and low steady-state EMSE values. The theoretical results are in good agreement with simulation results. Computer simulation results on AEC show that the R-QRRLM and VR-QRRLM algorithms considerably outperform the traditional RLS algorithm when the input signal level is low or during double talk. © 2010 IEEE.published_or_final_versio

Effect of the sound of dental equipment on dental anxiety and noise control techniques

The dental office environment subjects both patients and dental professionals to the noises associated with dental equipment. The sound of the dental drill, for example, usually causes some discomfort and anxiety. Fear and anxiety due to these noises are among the major reasons why patients avoid dental visits. It is important that these fears are addressed and patients are encouraged to seek the oral healthcare treatment they need. Long-term exposure to these noises also puts dental professionals themselves at high risk of hearing loss. It is unclear about the psychological influence of the sound of dental equipment on dental anxiety. This paper presents a questionnaire survey previously conducted by the authors to study the effects of the sound of dental equipment on people’s perceptions and dental anxiety levels and discusses solutions to the problem by means of passive and active noise control technologies or a combination of both of them.published_or_final_versio

A new switch-mode noise-constrained transform domain NLMS adaptive filtering algorithm

The transform domain normalized least mean squares (TDNLMS) algorithm is an efficient adaptive algorithm, which offers fast convergence speed with a reasonably low arithmetic complexity. However, its convergence speed is usually limited by the fixed step-size so as to achieve a low desired misadjustment. In this paper a new switch-mode noise-constrained TDNLMS (SNC-TDNLMS) algorithm is proposed. It employs a maximum step-size mode in initial convergence and a noise-constrained mode afterwards to improve the convergence speed and steady-state performance. The mean and mean square convergence behaviors of the proposed algorithm are studied to characterize its convergence condition and steady-state excess mean square error (EMSE). Based on the theoretical results, an automatic threshold selection scheme for mode switching is developed. Computer simulations are conducted to show the effectiveness of the proposed algorithm and verify the theoretical results. © 2011 IEEE.published_or_final_versionThe 2011 IEEE International Symposium on Circuits and Systems (ISCAS), Rio de Janeiro, Brazil, 15-18 May 2011. In Proceedings of ISCAS, 2011, p. 117-12

A New Compact and High Gain Circularly-Polarized Slot Antenna Array for Ku-Band Mobile Satellite TV Reception

© 2013 IEEE. A compact and high-gain SIW-fed circularly polarized (CP) slot-antenna array with a stacked feed structure is presented for the application of Ku-band high-data-rate satellite communications. First, a novel probe-fed SIW cavity with four slots etched on the top surface is proposed as a high-gain radiating element for the array. The four slots in the cavity act as a 2\times2 array, and its directivity is 2.15 and 1.43 dB greater than that of the cavity-backed antenna of the same size using ring slot and split ring slot, respectively. Second, a compact 1-4 SIW power divider is designed for exciting a subarray. Third, the 2\times2 subarray is further expanded to an 8\times16 array by adopting an additional layer of 1-32 SIW feeding network to meet the gain requirement of the Ku-band mobile satellite TV reception. Finally, experiments are carried out to verify the designed prototypes. Measured results show that proposed 128-element array has a relative impedance bandwidth of 4.8% (11.84 to 12.42 GHz), AR bandwidth of 130 MHz (12.01 to 12.14 GHz), and a peak gain of 26.8 dBic at 12.06 GHz. Owing to the simple feeding networks and the compact radiating element, the antenna has a compact size of 6.04\lambda 0 \times 11.96\lambda 0 \times 0.1\lambda 0. Experimental results show that the proposed CP antenna array is suitable for applications of Ku-band mobile satellite TV reception

New sequential partial update switch-mode noise-constrained nlms adaptive filtering algorithms

The sequential partial update LMS (S-LMS)-based algorithms are efficient adaptive filtering algorithms for reducing the high arithmetic complexity in acoustic and related applications. A limitation of the algorithms is the degraded convergence speed. In this paper, a new family of sequential partial update switch-mode noise-constrained NLMS (S-SNCNLMS) algorithms is proposed. These algorithms use a new variable step-size (VSS) method to increase the convergence speed of the traditional partial update algorithms while achieving the same steady-state excess mean square error (EMSE). It employs a maximum step-size to improve the initial convergence and exploits the prior knowledge of the additive noise variance as in the noise-constrained (NC) approach near convergence. The mean and mean square convergence behaviors of these new switch mode algorithms are studied to characterize its convergence condition and steady-state EMSE. Based on the theoretical results, an automatic threshold selection method for mode switching is also developed. Computer simulations are conducted to verify the theoretical results and effectiveness of the proposed algorithms. ©2010 IEEE.published_or_final_versionThe 10th International Symposium on Communications and Information Technologies (ISCIT 2010), Tokyo, Japan, 26-29 October 2010. In Proceedings of 10th ISCIT, 2010, p. 435-44

Identification of genes differentially expressed in Jining Grey and Liaoning Cashmere goats ovaries

To search for genes controlling high prolificacy of Chinese indigenous goats, differential display reverse transcription-polymerase chain reaction (DDRT-PCR) was used to screen differentially expressed cDNA bands in the sexually matured ovaries of 3-year-old prolific Jining Grey goats and monotocous Liaoning Cashmere goats with 24 combinations of three anchored primers and eight arbitrary primers. 22 expressed sequence tags (ESTs) were proved to be the positive bands by Northern hybridization. They comprised 10 known ESTs and 12 ESTs without homologous sequences in the GenBank. These results indicate that several genes such as GATA-4, metallothionein-like protein, CAT genes and unknown ESTs (CV983340 and CV983341) were expressed only in Jining Grey goats.Keywords: Differential display reverse transcription-polymerase chain reaction, goat, ovary, prolificacyAfrican Journal of Biotechnology Vol. 12(27), pp. 4408-441

Papillary carcinoma arising in a thyroglossal duct cyst with associated microcarcinoma of the thyroid and without cervical lymph node metastasis: a case report

<p>Abstract</p> <p>Introduction</p> <p>This is a case report of a 44-year-old woman with papillary carcinoma of a thyroglossal duct cyst.</p> <p>Case presentation</p> <p>A 44 year-old woman presented to the otolaryngology outpatient clinic with an asymptomatic anterior midline neck mass. A cervical ultrasound showed a lesion which appeared to be a thyroglossal duct cyst and surgical resection using Sistrunk's procedure was performed. The histopathologic diagnosis showed papillary carcinoma evolving from a thyroglossal duct cyst, confined to the thyroglossal cyst, with a tumor diameter of 2 cm. The patient then underwent total thyroidectomy and bilateral neck dissection. The final pathology reported an 8 mm papillary cancer in the left lobe of the thyroid without any metastasis to the cervical lymph nodes. The patient was treated with radioactive iodide and thyroid suppresion therapy was given as adjuvant treatment. The patient has been following for two years without any metastasis.</p> <p>Conclusion</p> <p>Malignancy within a thyroglossal duct cyst is very rare but should be considered in the differential diagnosis of a midline neck mass.</p