CP

The PLL is a feedback system used to generate clock signal in microprocessors, and frequency multiplication (FM) etc., The PLL consists of several components such as Phase frequency detector (PFD), Charge pump (CP), low pass filter (LPF), voltage controlled oscillator (VCO) and frequency divider (FD) circuits. The struck at single-event-effects (SEEs) such as latch-up, single-event-transient and multiple bit upsets which affect the PLL performance. PFD and FD which are free from dead zone due to their digital characteristics but the CP are affected by SEEs which causes the CP output to be degraded and which affect the VCO input hence PLL will lose lock. The PLL and its components are implemented in cadence virtuoso tool using 180nm technology.

In this work, the influence of the cyclic prefix on the performance of the OFDM system is studied. We worked out an OFDM transceiver using a 16 QAM modulation scheme, a comparison of the BER for various lengths of the cyclic prefix has been achieved, and the influence of the noise introduced in the channel has been highlighted, for both a Gaussian and Rayleigh noise. The simulation was carried out on MATLAB where the curves of the BER for various lengths of the cyclic prefix are given and compared. We also adopted as a metric the QAM constellation to show the dispersion of the carriers as a consequence of the transmission channel, the mitigation of this effect by the CP is noticeable.

ABSTRACT. The present paper introduces a new nonlocal coupled damage-plasticity model aiming at predicting crack paths within plates made of ductile material and subjected to pure tensile loading. This model is inspired by Nguyen's model [1] for quasi-brittle material. It uses the Houlsby and Puzrin [2] framework that makes the model formulation internally consistent by linking the damage and the yield functions via a dissipation potential. However, as in Lemaitre [3], the damage law is explicitly defined in order to ease the implementation. This ...

SICS is investigating a new generation of languages for symbolic processing that are based on the paradigm of concurrent constraint programming. A wide range of pertinent topics are being studied. In particular our e orts are devoted to producing a high quality programming environment based on the Andorra Kernel Language (AKL), a general purpose concurrent constraint language.

Recomplementation is a cover term for two distinct phenomena, related with COMP doubling in embedded clauses in the Iberoromance languages. The first is recomplementation in indicative clauses, where the second complementizer (que2) is used to set the boundaries between a reproduced discourse and the clausal elements that were implicit in the original discourse, which must be reintroduced in the new communicative situation because they are not shared by the interlocutor. The second is recomplementation in subjunctive clauses, which corresponds to a jussive/imperative clause in indirect speech, where a prominent element appears on the left periphery between the subordinating particle que1 and the obligatory jussive particle que2'.

Monotone literal fixing (MLF) and learning are well-known lookahead and lookback mechanisms in propositional satisfiability (SAT). When considering Quantified Boolean Formulas (QBFs), their separate implementation leads to significant speed-ups in state-of-the-art DPLL-based solvers. This paper is dedicated to the efficient implementation of MLF in a QBF solver with learning. The interaction between MLF and learning is far from being obvious, and it poses some nontrivial questions about both the detection and the propagation of monotone literals. Complications arise from the presence of learned constraints, and are related to the question about whether learned constraints have to be considered or not during the detection and/or propagation of monotone literals. In the paper we answer to this question both from a theoretical and from a practical point of view. We discuss the advantages and the disadvantages of various solutions, and show that our solution of choice, implemented in our solver QuBE, produces significant speed-ups in most cases. Finally, we show that MLF can be fundamental also for solving some SAT instances, taken from the 2002 SAT solvers competition.

We introduce the SomeDifferent constraint as a general- ization of AllDifferent. SomeDifferent requires that values assigned to some pairs of variables will be different. It has many practical ap- plications. For example, in workforce management, it may enforce the requirement that the same worker is not assigned to two jobs which are overlapping in time. Propagation of the constraint for hyper-arc consis- tency is NP hard. We present a propagation algorithm with worst case time complexity O(n3βn )w heren is the number of variables and β ≈ 3.5 (ignoring a trivial dependence on the representation of the domains). We also elaborate on several heuristics which greatly reduce the algorithm's running time in practice. We provide experimental results, obtained on a real-world workforce management problem and on synthetic data, which demonstrate the feasibility of our approach.

Recomplementation is a cover term for two distinct phenomena, related with COMP doubling in embedded clauses in the Iberoromance languages. The first is recomplementation in indicative clauses, where the second complementizer (que2) is used to set the boundaries between a reproduced discourse and the clausal elements that were implicit in the original discourse, which must be reintroduced in the new communicative situation because they are not shared by the interlocutor. The second is recomplementation in subjunctive clauses, which corresponds to a jussive/imperative clause in indirect speech, where a prominent element appears on the left periphery between the subordinating particle que1 and the obligatory jussive particle que2'.

In this paper we introduce a new method for bounding the solution to constraint optimization problems called semi-independent partitioning. We show that our method is a strict generalization of the mini buckets algorithm [1]. We demonstrate empirically that another specialization of SIP, called greedy SIP, generally produces a better answer than mini buckets in much less time.

Abstract. One of the most appealing features of constraint program-ming is its rich constraint language for expressing combinatorial opti-mization problems. This paper demonstrates that traditional combina-tors from constraint programming have natural counterparts for local ...