### Abstract

One of the disadvantages of the well known LMS FIR adaptive digital filter is that, for a colored noise input signals, the filter tends to converge slowly. One way to improve the convergence rate is to prefilter the input signal with an orthogonalizing transform, such as the Karhunen-Loeve transform (KLT). The transform domain LMS algorithm utilizes a discrete orthogonal transform such as the discrete Fourier transform (DFT), in an attempt to approximate the performance of the KLT. In addition to the DFT, this paper also considers the discrete cosine transform (DCT), the Walsh-Hadamard transform (WHT), and the discrete Hartley transform (DHT). Both the theoretical and experimental results seem to indicate that, when the numbers of quantization bits used by the transform domain filters are the same as those used by the time domain adaptive filter, the transform domain filters studied in this work perform as well as or even better than the time domain adaptive filter when the number of the coefficient bits is sufficiently larger than that of the data bits.

Original language | English (US) |
---|---|

Pages (from-to) | 228-232 |

Number of pages | 5 |

Journal | IEE Conference Publication |

Issue number | 308 |

State | Published - Dec 1 1989 |

Event | European Conference on Circuit Theory and Design - Brighton, Engl Duration: Sep 5 1989 → Sep 8 1989 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Electrical and Electronic Engineering

### Cite this

*IEE Conference Publication*, (308), 228-232.

}

*IEE Conference Publication*, no. 308, pp. 228-232.

**Analysis of fixed point roundoff effects in transform domain LMS adaptive filters.** / Jenkins, William Kenneth; Yun, J. K.

Research output: Contribution to journal › Conference article

TY - JOUR

T1 - Analysis of fixed point roundoff effects in transform domain LMS adaptive filters

AU - Jenkins, William Kenneth

AU - Yun, J. K.

PY - 1989/12/1

Y1 - 1989/12/1

N2 - One of the disadvantages of the well known LMS FIR adaptive digital filter is that, for a colored noise input signals, the filter tends to converge slowly. One way to improve the convergence rate is to prefilter the input signal with an orthogonalizing transform, such as the Karhunen-Loeve transform (KLT). The transform domain LMS algorithm utilizes a discrete orthogonal transform such as the discrete Fourier transform (DFT), in an attempt to approximate the performance of the KLT. In addition to the DFT, this paper also considers the discrete cosine transform (DCT), the Walsh-Hadamard transform (WHT), and the discrete Hartley transform (DHT). Both the theoretical and experimental results seem to indicate that, when the numbers of quantization bits used by the transform domain filters are the same as those used by the time domain adaptive filter, the transform domain filters studied in this work perform as well as or even better than the time domain adaptive filter when the number of the coefficient bits is sufficiently larger than that of the data bits.

AB - One of the disadvantages of the well known LMS FIR adaptive digital filter is that, for a colored noise input signals, the filter tends to converge slowly. One way to improve the convergence rate is to prefilter the input signal with an orthogonalizing transform, such as the Karhunen-Loeve transform (KLT). The transform domain LMS algorithm utilizes a discrete orthogonal transform such as the discrete Fourier transform (DFT), in an attempt to approximate the performance of the KLT. In addition to the DFT, this paper also considers the discrete cosine transform (DCT), the Walsh-Hadamard transform (WHT), and the discrete Hartley transform (DHT). Both the theoretical and experimental results seem to indicate that, when the numbers of quantization bits used by the transform domain filters are the same as those used by the time domain adaptive filter, the transform domain filters studied in this work perform as well as or even better than the time domain adaptive filter when the number of the coefficient bits is sufficiently larger than that of the data bits.

UR - http://www.scopus.com/inward/record.url?scp=0024876187&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0024876187&partnerID=8YFLogxK

M3 - Conference article

SP - 228

EP - 232

JO - IEEE Conference Publication

JF - IEEE Conference Publication

SN - 0537-9989

IS - 308

ER -