Constitutional developments since the Lisbon Treaty in the area of freedom, security and justice at supranational and national level

In order to evaluate the constitutional developments in the area of freedom, security and justice (AFSJ) of the Lisbon Treaty, this article begins with a tour d'horizon of the new provisions in the field of AFSJ. Their impact on the supranational and national constitutional legal order is discussed, and the differnces with the Treaty of Nice. There is also a review of some European Court of Justice cases interpreting the old Third Pillar instrument and comparing them with the new Lisbon challenges. Article by Alfred Kellermann (Senior EU Legal and Policy Advisor; Visiting Professor in European Law)

Early Parkes Observations of Planets and Cosmic Radio Sources

We discuss early Parkes observations of the radio emission from the planets Mercury, Venus, Mars, Saturn, and Uranus. The sensitive Parkes 11 cm system was used to detect a surprisingly high observed nighttime temperature on Mercury, the first, but unrecognized, hint that the Mercury actually rotates with respect to the Sun, as well as detecting the faint radio emission from Uranus. We also discuss the anomalous spectrum of PKS 1934-63, the first recognized GPS source.Comment: Published electronically in Proceedings "Science with Parkes @ 50 Years Young", 2012, Ed. Robert Braun. Conference link is, http://www.atnf.csiro.au/research/conferences/Parkes50th/ProcPapers/kellermann.pd

The NLMS algorithm with time-variant optimum stepsize derived from a Bayesian network perspective

In this article, we derive a new stepsize adaptation for the normalized least mean square algorithm (NLMS) by describing the task of linear acoustic echo cancellation from a Bayesian network perspective. Similar to the well-known Kalman filter equations, we model the acoustic wave propagation from the loudspeaker to the microphone by a latent state vector and define a linear observation equation (to model the relation between the state vector and the observation) as well as a linear process equation (to model the temporal progress of the state vector). Based on additional assumptions on the statistics of the random variables in observation and process equation, we apply the expectation-maximization (EM) algorithm to derive an NLMS-like filter adaptation. By exploiting the conditional independence rules for Bayesian networks, we reveal that the resulting EM-NLMS algorithm has a stepsize update equivalent to the optimal-stepsize calculation proposed by Yamamoto and Kitayama in 1982, which has been adopted in many textbooks. As main difference, the instantaneous stepsize value is estimated in the M step of the EM algorithm (instead of being approximated by artificially extending the acoustic echo path). The EM-NLMS algorithm is experimentally verified for synthesized scenarios with both, white noise and male speech as input signal.Comment: 4 pages, 1 page of reference