Network integration for international mergers and Acquisitions

Business activities are increasingly taking place across geographical and ownership boundaries. Post-Merger & Acquisition Integration (PMI) processes are more challenging in network organisations due to the extra complexity and interdependency associated with networks. However, network integration issues are not well addressed in the traditional M&A literature or the network organisation literature. Based on ten in-depth case studies across key industry sectors, this research identifies the essential network integration issues for international M&As with a configuration concept, and demonstrates different network integration patterns according to M&A objectives for growth and efficiency. This paper extends the theoretical understanding of PMI for network organisations. It can also provide practical guidance for managers to assess the feasibility of an M&A transition or to go through the PMI process successfully. Copyright © 2010 Inderscience Enterprises Ltd.

Multi-channel signal separation

The separation of independent sources from mixed observed data is a fundamental and challenging problem. In many practical situations, observations may be modelled as linear mixtures of a number of source signals, i.e. a linear multi-input multi-output system. A typical example is speech recordings made in an acoustic environment in the presence of background noise and/or competing speakers. Other examples include EEG signals, passive sonar applications and cross-talk in data communications. In this paper, we propose iterative algorithms to solve the n × n linear time invariant system under two different constraints. Some existing solutions for 2 × 2 systems are reviewed and compared.

Towards a perceptually optimal spectral amplitude estimator for audio signal enhancement

We present a statistical model-based approach to signal enhancement in the case of additive broadband noise. Because broadband noise is localised in neither time nor frequency, its removal is one of the most pervasive and difficult signal enhancement tasks. In order to improve perceived signal quality, we take advantage of human perception and define a best estimate of the original signal in terms of a cost function incorporating perceptual optimality criteria. We derive the resultant signal estimator and implement it in a short-time spectral attenuation framework. Audio examples, references, and further information may be found at http://www-sigproc.eng.cam.ac.uk/~pjw47.