A Comb Filter with Adaptive Notch Gain and Bandwidth
スポンサーリンク
概要
- 論文の詳細を見る
This paper proposes a new adaptive comb filter which automatically designs its characteristics. The comb filter is used to eliminate a periodic noise from an observed signal. To design the comb filter, there exists three important factors which are so-called notch frequency, notch gain, and notch bandwidth. The notch frequency is the null frequency which is aligned at equally spaced frequencies. The notch gain controls an elimination quantity of the observed signal at notch frequencies. The notch bandwidth controls an elimination bandwidth of the observed signal at notch frequencies. We have previously proposed a comb filter which can adjust the notch gain adaptively to eliminate the periodic noise. In this paper, to eliminate the periodic noise when its frequencies fluctuate, we propose the comb filter which achieves the adaptive notch gain and the adaptive notch bandwidth, simultaneously. Simulation results show the effectiveness of the proposed adaptive comb filter.
- The Institute of Electronics, Information and Communication Engineersの論文
著者
-
Kawamura Arata
Graduate School Of Engineering Science Osaka University
-
Iiguni Youji
Graduate School Of Engineering Science Osaka University
-
SUGIURA Yosuke
Graduate School of Engineering Science, Osaka University
関連論文
- Parallel Composition Based Adaptive Notch Filter : Performance and Analysis(Digital Signal Processing)
- Improvement of Speech Quality in Distance-Based Howling Canceller
- Moment Invariants of the Weighted Image
- Speech Enhancement Based on MAP Estimation Using a Variable Speech Distribution(Papers Selected from the 21st Symposium on Signal Processing)
- Image Enlargement by Nonlinear Frequency Extrapolation with Morphological Operators
- Shift-Invariant Sparse Image Representations Using Tree-Structured Dictionaries
- A High Speech Quality Distance-Based Howling Canceller with Adaptive Cascade Notch Filter and Silent Pilot Signal
- Convergence Vectors in System Identification with an NLMS Algorithm for Sinusoidal Inputs
- Convergence vector of normalized least-mean-square algorithm for predicting deterministic sinusoidal signals
- Supervised Single-Channel Speech Separation via Sparse Decomposition Using Periodic Signal Models
- Stationary and Non-stationary Wide-Band Noise Reduction Using Zero Phase Signal
- Supervised Single-Channel Speech Separation via Sparse Decomposition Using Periodic Signal Models
- Single channel blind source separation of deterministic sinusoidal signals with independent component analysis
- An Adaptation Method for Morphological Opening Filters with a Smoothness Penalty on Structuring Elements
- A Comb Filter with Adaptive Notch Gain and Bandwidth
- An Adaptive Comb Filter with Flexible Notch Gain