A subband Kalman filter for echo cancellation

This thesis involves the implementation of a Kalman filter for the application of echo cancellation. This particular Kalman filter is implemented in the frequency domain, in subbands, so as to make it faster and of lesser calculational complexity for real time applications. To evaluate the functioning of this subband Kalman filter, comparison of the performance of the subband Kalman filter is done with respect to the original time domain Kalman filter, and also with other subband adaptive filters for echo cancellation such as the NLMS filter. Additionally, since background noise affects the working of any adaptive filter, the newly developed subband Kalman filter\u27s performance at different noise conditions is compared, and an attempt to keep track of and predict this noise is also performed --Abstract, page iii

Development of Real-Time Adaptive Noise Canceller and Echo Canceller

In this paper, the adaptive cancellation structure is firstdeveloped based on the LMS algorithm and FIR adaptivefiltering. Then the novel practical noise and echo cancellationsystems are built using the proposed adaptive technique andimplemented using TX320TMS67C13 DSKs, which are TexasInstruments’ Digital Signal Processing (TI DSP) boards.Although adaptive filtering is an exciting topic in which manyreal-life applications can be explored [1]-[6], [9], building such areal-time system is often challenging due to the use of theoreticalmath, advanced DSP knowledge and practical industrial hands-onexperience [1],[4]-[6],[9]. Therefore, this paper indicates that it ispossible to apply traditional mathematics in adaptive filteringtheory to real-time practical DSP systems. With the MATLABsoftware tool, we can simulate and verify various adaptivefiltering designs first. Then, development and implementation ofdifferent noise or echo cancellation systems with adaptive filteringtechniques can be successfully performed using the floating-pointdigital signal processor, TX320TMS67C13 DSK. Furthermore, itcan be shown that TX320TMS67C13 DSKs with their stereochannels offer more effective and flexible tools for various noisecancellation applications

Implementasi Echo Cancellation Menggunakan Algoritma Adaptif NLMS Pada DSP Card Seri TMS320VC33-150

ABSTRAKSI: ABSTRAK Fenomena Echo yang muncul di alam dapat juga terjadi pada jaringan telekomunikasi suara. Menyebabkan terjadi penurunan nilai QoS dari suara. Echo disebabkan ketidak serasian impedansi hybrid saat penyambungan 2 kabel jaringan lokal menuju 4 kabel jaringan central, disebut Circuit echo. Implementasi untuk menghilangkan echo digunakan metode Echo Cancellation. Filter adaptif dengan struktur filter FIR sebagai dasar membangun echo cancellation. Koefisien filter diadaptasi algoritma NLMS yang mampu menurunkan gradien noise dari algoritma LMS. Echo pada hybrid dimodelkan oleh delay dan redaman (3.5dB), dikonvolusikan terhadap sinyal input. Filter adaptif dibangun dengan konvolusi sinyal input terhadap bobot sebatas N (nilai taps filter) dan menghasilkan echo estimasi. Sinyal echo hybrid dikurangkan dengan echo estimasi, bila sama besar maka menghasilakn output yang bersih dari echo. Tetapi bila tidak sama besar maka menghasilkan residu (error), sinyal error menjadi komponen pembentuk bobot pada algoritma adaptif NLMS untuk mengadaptasi koefisien pada filter adaptif. Dengan tujuan meminimalkan rata-rata dari MSE (Mean Square Error). TMS320VC33 merupakan DSP (Digital Signal Processor’s) Card dengan kecepatan operasi 13,34 ns per instruksi, sehingga memungkinkan sistem berjalan real time dan meminimalkan pengaruh delay. Setelah pengujian implementasi echo cancelllation pada TMS320VC33, maka dihasilkan nilai step size (µ) optimum pada µ=0.6, saat MSE bernilai paling minimum. Kemudian waktu proses berdasarkan perhitungan duty cycle sebesar 39.87 ms untuk taps filter minimum. Nilai ERL sebesar 5.24 dB (standar CCITT Rec G.131, 6 ± 2.5 dB) dan nilai ERLE sebesar 17.65 dB (standar ITU-T G.168, 20 dB). Hasil dari sistem echo cancellation yang diimplementasikan masih sesuai dengan standar nilai-nilaiKata Kunci : Echo Cancellation, NLMS, Step SIZE, Taps Filter, TMS320VC33-150ABSTRACT: ABSTRACT Echo phenomenon usually appear in nature, also can be happen in voice telecomunication network. Which could decraesing voice QoS value. Echo couses by hybrid impedance mis’match, when built connections 2-wire at local loop to 4-wire at central, wich known as Circuit echo. Implementation use Echo Cancellation methode to make echo disappear. Adaptive filter use FIR filter structure as basic to built echo cancellation. Filter coefficient adapted by NLMS algorithm which able to decrease gradien noise from algorithm LMS. Echo in hybrid, models by delay and attenuation (3.5dB), then convoluted with input signal. Adaptive filter build by convolutioning input signal with weight which limited by N (taps filter value), to produce estimation echo. Hybrid echo signal subtract with echo estimation signal, if both of the signal have a same value, then it will produce output free from echo. But if the substraction of those signal produce the remainder then it’ll built error signal. The error signal use as a component to produce new weigth at the NLMS adaptive algorithm. The new weigths are use to update filter adaptive coefficient. Which aim to minimalize the average of MSE. While TMS320VC33 is DSP (Digital Signal Processor’s) Card which has operation valocity 13,34 ns to excute one instruction, so there’s probability for the system to operate as a real time system and minimalize the delay effect. After examine the implementation of echo cancelllation at TMS320VC33, then resulting step size (µ) value optimum at µ = 0.6, when MSE value very minimum. Then time process reach 39.87 ms base on duty cycle calculation, for minimum taps filter in use. ERL value result 5.24 dB where the CCITT Rec G.131 standard, 6 ± 2.5 dB. Then ERLE value result 17.65 dB where the ERLE ITU-T G.168 standard, 20 dB. The result of the implementation echo cancellation in TMS320VC33 still in range of the standard parameter values.Keyword: Echo Cancellation, NLMS, Step SIZE, Taps Filter, TMS320VC33-15

MOTION ARTIFACT CANCELLATION IN AMBULATORY ECG MEASUREMENT SYSTEM FOR THE DETECTION OF CARDIAC DISEASES

Abstract-In this work, a simple and efficient artifact cancellation in ambulatory ECG using adaptive filter is designed for the detection of different cardiac diseases like bradycardia, tachycardia, left ventricular hypertrophy and right ventricular hypertrophy. Our work is focused on extraction of noise free ECG signal and the real-time implementation of artifacts removal techniques. As ECG signal is very sensitive in nature, and even if small noise mixed with original signal the various characteristics of the signal changes, data corrupted with noise must either filtered or discarded, filtering is important issue for design consideration of real-time ECG measurement systems. Here we have implemented different adaptive filtering algorithms (LMS-Least Mean Square, RLS-Recursive Least Squares) using virtual instrumentation technique to minimize the noisy components and to analyze different cardiac diseases like bradycardia, tachycardia, left ventricular hypertrophy and right ventricular hypertrophy. Finally the overall performance of LMS and RLS algorithm is also compared according to the error signal generated by the techniques

Dental drill noise reduction using a combination of active noise control, passive noise control and adaptive filtering

Dental drills produce a characteristic high frequency, narrow band noise that is uncomfortable for patients and is also known to be harmful to dentists under prolonged exposure. It is therefore desirable to protect the patient and dentist whilst allowing two-way communication. A solution is to use a combination of the three main noise control methods, namely, Passive Noise Control (PNC), Adaptive Filtering (AF) and Active Noise Control (ANC). This paper discusses the application of the three methods to reduce dental drill noise while allowing two-way communication. Experimental setup for measuring the noise reduction by PNC is explained and results from different headphones and headphone types are presented. The implementation and results of an AF system using the Least Mean Square (LMS) algorithm are shown. ANC requires a modification of the LMS algorithm due to the introduction of the electro-acoustical cancellation path transfer function to compensate for the delays introduced by the control system. Therefore a cancellation path transfer function modeling method based on the filtered reference LMS (FXLMS) algorithm is presented along with preliminary results of the implementation

Estimation-based synthesis of H∞-optimal adaptive FIR filtersfor filtered-LMS problems

This paper presents a systematic synthesis procedure for H∞-optimal adaptive FIR filters in the context of an active noise cancellation (ANC) problem. An estimation interpretation of the adaptive control problem is introduced first. Based on this interpretation, an H∞ estimation problem is formulated, and its finite horizon prediction (filtering) solution is discussed. The solution minimizes the maximum energy gain from the disturbances to the predicted (filtered) estimation error and serves as the adaptation criterion for the weight vector in the adaptive FIR filter. We refer to this adaptation scheme as estimation-based adaptive filtering (EBAF). We show that the steady-state gain vector in the EBAF algorithm approaches that of the classical (normalized) filtered-X LMS algorithm. The error terms, however, are shown to be different. Thus, these classical algorithms can be considered to be approximations of our algorithm. We examine the performance of the proposed EBAF algorithm (both experimentally and in simulation) in an active noise cancellation problem of a one-dimensional (1-D) acoustic duct for both narrowband and broadband cases. Comparisons to the results from a conventional filtered-LMS (FxLMS) algorithm show faster convergence without compromising steady-state performance and/or robustness of the algorithm to feedback contamination of the reference signal