New initialization methods for discrete coefficient FIR filter design with coefficient scaling and the use of scale factor in the design process

Date

2006-02-01

Author

Çiloğlu, Tolga

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

140
views

0
downloads

The initialization of filter coefficients in discrete-coefficient finite-impulse-response (FIR) filter design (with coefficient scaling) using coefficient-value-assignment-based optimization techniques is considered. A common weakness of existing initialization measures, a total-square-error (TSE) measure and a maximum-error (ME) measure, is described. New TSE and ME measures that overcome the weakness are introduced. As opposed to the current knowledge, it is revealed that TSE and ME measures do not necessarily provide different initial coefficient set information and that the initial coefficient set information by the ME measure is not unique in general. On a parallel track, the treatment of coefficient scaling in the optimization process is considered. The closed-form expression of the objective function normalized peak ripple magnitude (NPRM), which was defined implicitly in the literature, is given. In contrast to existing methods, the computation of NPRM accordingly does not require a scale-factor parameter independent of filter coefficients although coefficient scaling persists. Then, TSE and ME measures become practically equivalent (although, in general, they indicate different initial scale factors) since an explicit scale factor parameter is no longer needed.

Subject Keywords

Signal Processing, Electrical and Electronic Engineering

URI

https://hdl.handle.net/11511/38347

Journal

IEEE TRANSACTIONS ON SIGNAL PROCESSING

DOI

https://doi.org/10.1109/tsp.2005.861795

Collections

Department of Electrical and Electronics Engineering, Article

Suggestions

OpenMETU
Core

Robust adaptive unscented Kalman filter for attitude estimation of pico satellites Hacızade, Cengiz; Söken, Halil Ersin (Wiley, 2014-02-01) Unscented Kalman filter (UKF) is a filtering algorithm that gives sufficiently good estimation results for the estimation problems of nonlinear systems even when high nonlinearity is in question. However, in case of system uncertainty or measurement malfunctions, the UKF becomes inaccurate and diverges by time. This study introduces a fault-tolerant attitude estimation algorithm for pico satellites. The algorithm uses a robust adaptive UKF, which performs correction for the process noise covariance (Q-adapt...
Risk-sensitive particle filters for mitigating sample impoverishment Orguner, Umut (Institute of Electrical and Electronics Engineers (IEEE), 2008-10-01) Risk-sensitive filters (RSF) put a penalty to higher-order moments of the estimation error compared to conventional filters as the Kalman filter minimizing the mean square error (MSE). The result is a more cautious filter, which can be interpreted as an implicit and automatic way to increase the state noise covariance. On the other hand, the process of jittering, or roughening, is well known in particle filters to mitigate sample impoverishment. The purpose of this contribution is to introduce risk-sensitiv...
An efficient filtering structure for Lagrange interpolation Candan, Çağatay (Institute of Electrical and Electronics Engineers (IEEE), 2007-01-01) A novel filtering structure with linear complexity is proposed for Lagrange interpolation. The structure is similar to the Farrow structure in principle, but it is more efficient and has the additional feature of being order updatable on-the-fly. The main application for the proposed structure is the implementation of fractional delay filters to mitigate the symbol synchronization errors in digital communications. Some other applications are time-delay estimation, echo cancellation, acoustic modeling, and a...
A unified framework for derivation and implementation of Savitzky-Golay filters Candan, Çağatay (Elsevier BV, 2014-11-01) The Savitzky-Golay (SG) filter design problem is posed as the minimum norm solution of an underdetermined equation system. A unified SG filter design framework encompassing several important applications such as smoothing, differentiation, integration and fractional delay is developed. In addition to the generality and flexibility of the framework, an efficient SG filter implementation structure, naturally emerging from the framework, is proposed. The structure is shown to reduce the number of multipliers i...
Extended Target Tracking Using Polynomials With Applications to Road-Map Estimation Lundquist, Christian; Orguner, Umut; Gustafsson, Fredrik (Institute of Electrical and Electronics Engineers (IEEE), 2011-01-01) This paper presents an extended target tracking framework which uses polynomials in order to model extended objects in the scene of interest from imagery sensor data. State-space models are proposed for the extended objects which enables the use of Kalman filters in tracking. Different methodologies of designing measurement equations are investigated. A general target tracking algorithm that utilizes a specific data association method for the extended targets is presented. The overall algorithm must always ...

Citation Formats

T. Çiloğlu, “New initialization methods for discrete coefficient FIR filter design with coefficient scaling and the use of scale factor in the design process,” IEEE TRANSACTIONS ON SIGNAL PROCESSING, pp. 796–800, 2006, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/38347.