Developments in block copolymer science and technology

Focuses on recent advances in research on block copolymers, covering chemistry (synthesis), physics (phase behaviors, rheology, modeling), and applications (melts and solutions). Written by a team of internationally respected scientists from industry and academia, this text compiles and reviews the expanse of research that has taken place over the last five years into one accessible resource. Ian Hamley is the world-leading scientist in the field of block copolymer research Presents the recent advances in the area, covering chemistry, physics and applications. Provides a broad coverage from synthesis to fundamental physics through to applications Examines the potential of block copolymers in nanotechnology as self-assembling soft materials

Robust initialisation of Gaussian radial basis function networks using partitioned k-means clustering

Radial basis function networks can be trained quickly using linear optimisation once centres and other associated parameters have been initialised. The authors propose a small adjustment to a well accepted initialisation algorithm which improves the network accuracy over a range of problems. The algorithm is described and results are presented.

Robust blind deconvolution algorithm: variance approximation and series decoupling

An alternative blind deconvolution algorithm for white-noise driven minimum phase systems is presented and verified by computer simulation. This algorithm uses a cost function based on a novel idea: variance approximation and series decoupling (VASD), and suggests that not all autocorrelation function values are necessary to implement blind deconvolution.

Technique for micro-machining millimetre-wave rectangular waveguide

A new technique is reported for micro-machining millimetre-wave rectangular waveguide components. S-parameter measurements on these structures show that they achieve lower loss than those produced using any other on-chip fabrication technique, have highly accurate dimensions, are physically robust, and are cheap and easy to manufacture.

Integrating predictive control and economic optimisation

In most commercially available predictive control packages, there is a separation between economic optimisation and predictive control, although both algorithms may be part of the same software system. This method is compared in this article with two alternative approaches where the economic objectives are directly included in the predictive control algorithm. Simulations are carried out using the Tennessee Eastman process model.