Programmable active memories in real-time tasks: implementing data-driven triggers for LHC experiments

The future Large Hadron Collider (LHC), to be built at CERN, presents among other technological challenges a formidable problem of real-time data analysis. At a primary event rate of 40 MHz, a multi-stage trigger system has to analyze data to decide which is the fraction of events that should be preserved on permanent storage for further analysis. We report on implementations of local algorithms for feature extraction as part of triggering, using the detectors of the proposed ATLAS experiment as a model. The algorithms were implemented for a decision frequency of 100 kHz, on different data-driven programmable devices based on structures of field- programmable gate arrays and memories. The implementations were demonstrated at full speed with emulated input, and were also integrated into a prototype detector running in a test beam at CERN, in June 1994

Pattern Comparator Trigger (PACT) for the muon system of the CMS experiment

The general scheme for the fast, pipelined first level trigger on high pt muons in the CMS detector at LHC is presented. The prototype PACT system was tested in the high momentum muon beams in the RD5 experiment during 1993/94 runs. The obtained efficiency curves are shown

Inclusive V0V^0 Production Cross Sections from 920 GeV Fixed Target Proton-Nucleus Collisions

Inclusive differential cross sections $d\sigma_{pA}/dx_F$ and $d\sigma_{pA}/dp_t^2$ for the production of \kzeros, \lambdazero, and \antilambda particles are measured at HERA in proton-induced reactions on C, Al, Ti, and W targets. The incident beam energy is 920 GeV, corresponding to $\sqrt {s} = 41.6$ GeV in the proton-nucleon system. The ratios of differential cross sections \rklpa and \rllpa are measured to be $6.2\pm 0.5$ and $0.66\pm 0.07$, respectively, for \xf $\approx-0.06$. No significant dependence upon the target material is observed. Within errors, the slopes of the transverse momentum distributions $d\sigma_{pA}/dp_t^2$ also show no significant dependence upon the target material. The dependence of the extrapolated total cross sections $\sigma_{pA}$ on the atomic mass $A$ of the target material is discussed, and the deduced cross sections per nucleon $\sigma_{pN}$ are compared with results obtained at other energies.Comment: 17 pages, 7 figures, 5 table

The QCD transition temperature: results with physical masses in the continuum limit II.

We extend our previous study [Phys. Lett. B643 (2006) 46] of the cross-over temperatures (T_c) of QCD. We improve our zero temperature analysis by using physical quark masses and finer lattices. In addition to the kaon decay constant used for scale setting we determine four quantities (masses of the \Omega baryon, K^*(892) and \phi(1020) mesons and the pion decay constant) which are found to agree with experiment. This implies that --independently of which of these quantities is used to set the overall scale-- the same results are obtained within a few percent. At finite temperature we use finer lattices down to a <= 0.1 fm (N_t=12 and N_t=16 at one point). Our new results confirm completely our previous findings. We compare the results with those of the 'hotQCD' collaboration.Comment: 19 pages, 8 figures, 3 table

Vorrichtung und Verfahren zum Erzeugen eines gefilterten Aktivitätsmusters, Quellentrenner, Verfahren zum Erzeugen eines bereinigten Audiosignals und Computerprogramm

DE 102006030276 A1 UPAB: 20080128 NOVELTY - The device (100) comprises an identifier (120) for identifying one trajectory in the one activity pattern and other trajectory in the other activity pattern, which are associated with the same sound event. The device has a filter (140) for filtering the one activity pattern or the other activity pattern based on a result of the determinator as to whether a trajectory is associated with a sound event of the wanted sound source, so that in the filtered activity pattern activity events that are associated with a sound event of the wanted sound source dominate. USE - Used for producing a filtered activity pattern, which is based on a activity pattern on a hearing model of an ear and another activity pattern on a hearing model of another ear. ADVANTAGE - The device enables a determination of a filter activity pattern in an efficient, reliable and hearing-adjusted manner, so that in the filtered activity pattern a wanted sound source is emphasized, while interference sound sources are suppressed or damped

Verfahren, Vorrichtung und Computerprogramm zum Erzeugen eines Ansteuersignals für ein Cochlea-Implantat basierend auf einem Audiosignal

The invention relates to a method for generating a control signal for a cochlea implant based on an audio signal, comprising a calculation (110) of first information on an activity pattern over time of a number of internal hair cells of an auditive model, arising from the audio signal. The method further comprises a filtering (120) of activity events described by the first information based on a recognition of a characteristic pattern in the activity pattern to give corrected information. The corrected information is then used as control signal for the cochlea implant, or the control signal is derived from the corrected information. Said method can be carried out by a computer programme or a corresponding device. By means of the above, for example, the auditive impression for patients with a cochlea implant can be significantly improved. A filtering of activity events, based on the recognition of a characteristic pattern in the activity pattern is particularly suitable to human hearing and permits the control of a cochlea implant such that the best possible speech recognition with the least possible energy use of a cochlea implant is achieved

Modeling the formation process of grouping stimuli sets through cortical columns and microcircuits to feature neurons

A computational model of a self-structuring neuronal net is presented in which repetitively applied pattern sets induce the formation of cortical columns and microcircuits which decode distinct patterns after a learning phase. In a case study, it is demonstrated how specific neurons in a feature classifier layer become orientation selective if they receive bar patterns of different slopes from an input layer. The input layer is mapped and intertwined by self-evolving neuronal microcircuits to the feature classifier layer. In this topical overview, several models are discussed which indicate that the net formation converges in its functionality to a mathematical transform which maps the input pattern space to a feature representing output space. The self-learning of the mathematical transform is discussed and its implications are interpreted. Model assumptions are deduced which serve as a guide to apply model derived repetitive stimuli pattern sets to in vitro cultures o f neuron ensembles to condition them to learn and execute a mathematical transform