Optimal Design of Magnitude Responses of Rational Infinite Impulse Response Filters

Ho, Charlotte Yuk-Fan; Ling, Bingo Wing‐Kuen; Liu, Yanping; Tam, P.K.S.; Teo, K.L.

doi:10.1109/tsp.2006.880317

Cited by 17 publications

(15 citation statements)

References 28 publications

(28 reference statements)

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“…Following the approach described in [16], the transfer function can be expressed in the so-called polar form as (3) where the and are the zero and pole radii and and are the corresponding angles in the plane, respectively, and 4Although (1) and 3are equivalent, there are, nevertheless, significant differences when performing the optimization, notably in the evaluation of the constraint matrices. Consequently, the performance of the optimization algorithm as well as that of the resulting digital filters can be affected as will be discussed in Section VI.…”

Section: Problem Formulationmentioning

confidence: 99%

“…On the other hand, MATLAB ® function iirlpnormc in [2] implements a least-th Newton method that uses barrier constraints to assure the stability of the resulting filter. A more recent method reported in [3] uses a constraint transcription method to achieve an efficient solution of a non-smooth non-convex objective function with continuous functional constraints. Since there is no restriction on the resulting phase response, these methods generally yield a better magnitude response than methods that also optimize the phase response.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Design Methodology for Nearly Linear-Phase Recursive Digital Filters by Constrained Optimization

Guindon

Shpak

Antoniou

2010

IEEE Trans. Circuits Syst. I

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A methodology for the design of recursive digital filters having nearly linear phase response is proposed. The underlying design method is of the direct type whereby the filter is designed as a single unit. The design problem is formulated as a cascade of filter sections where each section is represented by a biquadratic transfer function either in the conventional polynomial form or in the polar form. The design problem is then solved using a constrained Newton's method whereby constraints are used to assure the stability of the filter, to control the step size in order to achieve fast convergence, and to eliminate a real-axis pole-migration problem that often interferes with the design process. Several design examples demonstrate that when compared with filters designed using existing state-of-the-art methods, the proposed methodology yields filters having reduced order and/or improved performance.

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Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design Methodology for Nearly Linear-Phase Recursive Digital Filters by Constrained Optimization

Guindon

Shpak

Antoniou

2010

IEEE Trans. Circuits Syst. I

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show abstract

“…Compared to the problem discussed in [15], in which it consists of a smooth cost function, the method used in [15] cannot be applied to solve this optimization problem. To solve this optimization problem,…”

Section: Notationsmentioning

confidence: 99%

Design of Near-Allpass Strictly Stable Minimal-Phase Real-Valued Rational IIR Filters

Ling

Chi

et al. 2008

IEEE Trans. Circuits Syst. II

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Abstract-In this brief, a near allpass strictly stable minimal phase real valued rational IIR filter is designed so that the maximum absolute phase error is minimized subject to a specification on the maximum absolute allpass error. This problem is actually a minimax nonsmooth optimization problem subject to both linear and quadratic functional inequality constraints. To solve this problem, the nonsmooth cost function is first approximated by a smooth function and then our previous proposed method is employed for solving the problem. Computer numerical simulation result shows that the designed filter satisfies all functional inequality constraints and achieves a small maximum absolute phase error.Index Terms-Strictly stable, minimal phase, near allpass, real valued rational IIR filters, functional inequality constraints, minimax nonsmooth optimization problem.

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“…An iterative power allocation scheme is developed in [3]. It employs theNash equilibrium (NE) theory for solving the non-convex optimization problem [4], [5]. Here, the objective function is to maximizethe capacity.…”

Section: Introductionmentioning

confidence: 99%

Problem formulation for joint cooperative downlink scheduling and power allocation for joint processing coordinated multipoint

Hooshmand

Aghvami

Ling³

2014

2014 IEEE International Conference on Consumer Electronics - China

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The true potential of the orthogonal frequency divisional multiple access (OFDMA)coordinated multipoint (CoMP) is in turning the adverse effects of the inter-cell interference (ICI) into the system performance gains. The small ultradense deployments of data-hungry users in the forthcoming generations of wireless mobile access systems, namely the long term evolution (LTE) A as 4G and the subsequent 5G, will be pushing for the revolutionary innovations to accommodate the required peak rates and the reliability in the cell edge. CoMP has been identified as a competent solution to exploit the interference in the cell-edge. To this end, we consider the non-coherent joint processing (JP) mode of CoMP in the downlink (DL) of an LTE system. Here, we formulate the problem of the joint cooperative scheduling and transmit power allocationas a hybrid mixed integer non-convex optimization problem. In particular, the transmit power allocation is based on the allocation of the time-frequency resources according to a proportionally fair (PF) utility function with certain CoMPspecific constraints on the transmission.This problem formulation serves a twofold purpose of both the interference coordination under a full frequency reuse regime and the inherent interference mitigation capabilities.

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Optimal Design of Magnitude Responses of Rational Infinite Impulse Response Filters

Cited by 17 publications

References 28 publications

Design Methodology for Nearly Linear-Phase Recursive Digital Filters by Constrained Optimization

Design Methodology for Nearly Linear-Phase Recursive Digital Filters by Constrained Optimization

Design of Near-Allpass Strictly Stable Minimal-Phase Real-Valued Rational IIR Filters

Problem formulation for joint cooperative downlink scheduling and power allocation for joint processing coordinated multipoint

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