Enhanced cognition‐driven formulation of space mapping for equal‐ripple optimisation of microwave filters. Issue 1 (6th December 2017)

• Record Type: Journal Article
• Authors: Zhang, Chao; Feng, Feng; Zhang, Qi‐Jun; Bandler, John W.
• Is Part Of: IET microwaves, antennas & propagation. Volume 12:Issue 1(2018)
• Page Start: 82
• Page End: 91
• Publication Date: 2017-12-06
• Subjects: microwave filters -- optimisation -- cognition -- band‐pass filters -- Chebyshev filters; enhanced cognition‐driven formulation -- space mapping -- equal‐ripple optimisation -- microwave filter -- feature frequency parameter -- ripple height parameter -- equally divided passband specification -- Chebyshev filter function -- cognition‐driven SM; Microwaves -- Periodicals; Microwave antennas -- Periodicals; Antennas (Electronics) -- Periodicals; Radio wave propagation -- Periodicals; Microwave communication systems -- Periodicals; 621.381305
• DOI: 10.1049/iet-map.2017.0238
• Languages: English
• ISSNs: 1751-8725

Abstract

Abstract : A recently introduced cognition‐driven formulation of space mapping (SM) is an efficient method for equal‐ripple optimisation of microwave filters. Feature frequency parameters and ripple height parameters are utilised. The technique requires the assumption that the initial number of feature parameters is correct, and uses an equally divided passband specification as a preliminary target. The present study proposes an enhanced technique which can correct the number of feature frequency parameters, thus it can work well even if the filter response of the initial point has an incorrect number of feature frequency parameters. Additionally, the enhanced technique incorporates filter design knowledge of the Chebyshev filter function into cognition‐driven SM. The authors propose to use the feature frequency parameters of the Chebyshev filter function response curve to obtain the target for cognition‐driven SM. A new trust region mechanism handles new parameters in the proposed process of correcting the number of feature frequency parameters and guarantees convergence. The technique is suitable for the design of filters with equal‐ripple responses. It is illustrated by two microwave filter examples.