• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.240-240
• /
• 2000

This paper presents two algorithms based on the concept of the frequency domain adaptive filter(FDAF). First the frequency domain recursive least squares(FRLS) algorithm with the overlap-save filtering technique is introduced. This minimizes the sum of exponentially weighted square errors in the frequency domain. To eliminate discrepancies between the linear convolution and the circular convolution, the overlap-save method is utilized. Second, the sliding method of data blocks is studied Co overcome processing delays and complexity roads of the FRLS algorithm. The size of the extended data block is twice as long as the filter tap length. It is possible to slide the data block variously by the adjustable hopping index. By selecting the hopping index appropriately, we can take a trade-off between the convergence rate and the computational complexity. When the input signal is highly correlated and the length of the target FIR filter is huge, the FRLS algorithm based on the block processing technique has good performances in the convergence rate and the computational complexity.

• Proceedings of the KIEE Conference
• /
• 1991.11a
• /
• pp.374-377
• /
• 1991

In this paper, it is proposed to improve the robustness of the Fast Recursive Least Squares(FRLS) algolithms with the exponential weighting, which is an important class of algolithms for adaptive filtering. It is well known that the FRLS algolithm is numerically unstable with exponential weighting factor ${\lambda}<1$. However, introducing some gains into this algolithms, numerical errors can be reduced. An accurately choice of the gains then leads to a numerically stable FRLS algolithm with a complexity of 8m multiplications and we shown it by computer simulations.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1991.06a
• /
• pp.28-31
• /
• 1991

In this paper, it is proposed to improve the robustness of the Fast Recursive Least Squarea(FRLS) algolithms with the exponential weighting, which is an important class of algolithms for adaptive filtering. It is well known that the FRLSalgolithm is numerically unstable with exponential weighting factor λ<1. However, introducing some gains into this algolithms, numerical errors can be reduced. An accurately choice of thegains then leads to a numerically stable FRLS algolithm with a complexity of 8m mulitiplications and we shown it by computer simulations.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.19 no.2
• /
• pp.373-380
• /
• 1994

In this paper, we proposed a method of extracting optimum features of speech signal to adjust signal level. For extracting features of speech signal we used FRLS(Fast Recursive Least Square) algorithm, we adjusted each frames of equal to constant level, and extracted optimum features of speech signal by using equalized autocorrelation function proposed in this paper.

• Journal of Nutrition and Health
• /
• v.56 no.5
• /
• pp.573-588
• /
• 2023

Purpose: This study aimed to examine social networking service (SNS) use and recommended information utilization (SURU) according to the food-related lifestyles (FRLs) of consumers and analyze how the interaction between the FRL and SURU affects the practice of eating alone and visiting restaurants. Methods: Data on 4,624 adults in their 20s to 50s were collected from the 2021 Consumer Behavior Survey for Food. Statistical methods included factor analysis, K-means cluster analysis, the complex samples general linear model, the complex samples Rao-Scott χ² test, and the general linear model. Results: The following three factors were extracted from the FRL data: Convenience pursuit, rational consumption pursuit, and gastronomy pursuit, and the subjects were classified into three groups, namely the rational consumption, convenient gastronomy, and smart gourmet groups. An examination of the difference in SURU according to the FRL showed that the smart gourmet group had the highest score. The result of analyzing the effects of the FRL and SURU on eating alone revealed that both the main effect and the interaction effect were significant (p < 0.01, p < 0.001). The higher the SURU, the higher the frequency of eating alone in the convenience pursuit, and gastronomy pursuit groups. The main and interaction effects of the FRL and SURU on the frequency of eating out were also significant (p < 0.01, p < 0.001). In all the FRL groups, the higher the SURU level, the higher the frequency of visiting restaurants. Specifically, the two groups with convenience and gastronomic tendencies showed a steeper increase. Conclusion: This study provides important basic data for research on consumer behavior related to food SNS, market segmentation of restaurant consumers, and development of marketing strategies using SNS in the future.