Improve Akaikes Information Criterion Estimation Based onDenoising of Quadrature Mirror Filter Bank
Akaikes Information Criterion (AIC) is a popular method for estimation the number of sources impinging on an array of sensors, which is a problem of great interest in several applications. The performance of AIC degrades under low Signal-to-Noise Ratio (SNR). This paper is concerned with the develop...
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| Formato: | article |
| Lenguaje: | EN |
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Al-Khwarizmi College of Engineering – University of Baghdad
2009
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/6b036e92ed3b49fa84834ec47a5bde88 |
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| Sumario: | Akaikes Information Criterion (AIC) is a popular method for estimation the number of sources impinging on an array of sensors, which is a problem of great interest in several applications. The performance of AIC degrades under low Signal-to-Noise Ratio (SNR). This paper is concerned with the development and application of quadrature mirror filters (QMF) for improving the performance of AIC. A new system is proposed to estimate the number of sources by applying AIC to the outputs of filter bank consisting quadrature mirror filters (QMF). The proposed system can estimate the number of sources under low signal-to-noise ratio (SNR). |
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