954 resultados para Continuous-time sigma-delta modulation


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In this paper we consider a stochastic process that may experience random reset events which suddenly bring the system to the starting value and analyze the relevant statistical magnitudes. We focus our attention on monotonic continuous-time random walks with a constant drift: The process increases between the reset events, either by the effect of the random jumps, or by the action of the deterministic drift. As a result of all these combined factors interesting properties emerge, like the existence (for any drift strength) of a stationary transition probability density function, or the faculty of the model to reproduce power-law-like behavior. General formulas for two extreme statistics, the survival probability, and the mean exit time, are also derived. To corroborate in an independent way the results of the paper, Monte Carlo methods were used. These numerical estimations are in full agreement with the analytical predictions.

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Tässä työssä tutkitaan D-luokan audiovahvistimen pääteastetopologioiden eroja teknisen toiminnan, käytännön toteutuksen ja audiosignaalin laadun näkökulmista. Tutkimuksen perusteella valitaan yksi topologia kitaravahvistinsovellukseen, jossa modulointi on toteutettu Sigma-Delta-modulaattorilla. Pääteastetopologioiden tekninen toiminta selvitetään yksityiskohtaisesti virtojen kulkureittien avulla. Simulaatioilla tutkitaan suoja-ajan ja tulosignaalin variaatioiden vaikutusta lähtösignaalin kokonaisharmoniseen säröön (THD) ja selvitetään signaalin säröytymiseen vaikuttavien tekijöiden syitä D-luokan vahvistimen pääteasteessa.

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This dissertation describes a networking approach to infinite-dimensional systems theory, where there is a minimal distinction between inputs and outputs. We introduce and study two closely related classes of systems, namely the state/signal systems and the port-Hamiltonian systems, and describe how they relate to each other. Some basic theory for these two classes of systems and the interconnections of such systems is provided. The main emphasis lies on passive and conservative systems, and the theoretical concepts are illustrated using the example of a lossless transfer line. Much remains to be done in this field and we point to some directions for future studies as well.

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In a sigma-delta analog to digital (A/D) As most of the sigma-delta ADC applications require converter, the most computationally intensive block is decimation filters with linear phase characteristics, the decimation filter and its hardware implementation symmetric Finite Impulse Response (FIR) filters are may require millions of transistors. Since these widely used for implementation. But the number of FIR converters are now targeted for a portable application, filter coefficients will be quite large for implementing a a hardware efficient design is an implicit requirement. narrow band decimation filter. Implementing decimation In this effect, this paper presents a computationally filter in several stages reduces the total number of filter efficient polyphase implementation of non-recursive coefficients, and hence reduces the hardware complexity cascaded integrator comb (CIC) decimators for and power consumption [2]. Sigma-Delta Converters (SDCs). The SDCs are The first stage of decimation filter can be operating at high oversampling frequencies and hence implemented very efficiently using a cascade of integrators require large sampling rate conversions. The filtering and comb filters which do not require multiplication or and rate reduction are performed in several stages to coefficient storage. The remaining filtering is performed reduce hardware complexity and power dissipation. either in single stage or in two stages with more complex The CIC filters are widely adopted as the first stage of FIR or infinite impulse response (IIR) filters according to decimation due to its multiplier free structure. In this the requirements. The amount of passband aliasing or research, the performance of polyphase structure is imaging error can be brought within prescribed bounds by compared with the CICs using recursive and increasing the number of stages in the CIC filter. The non-recursive algorithms in terms of power, speed and width of the passband and the frequency characteristics area. This polyphase implementation offers high speed outside the passband are severely limited. So, CIC filters operation and low power consumption. The polyphase are used to make the transition between high and low implementation of 4th order CIC filter with a sampling rates. Conventional filters operating at low decimation factor of '64' and input word length of sampling rate are used to attain the required transition '4-bits' offers about 70% and 37% of power saving bandwidth and stopband attenuation. compared to the corresponding recursive and Several papers are available in literature that deals non-recursive implementations respectively. The same with different implementations of decimation filter polyphase CIC filter can operate about 7 times faster architecture for sigma-delta ADCs. Hogenauer has than the recursive and about 3.7 times faster than the described the design procedures for decimation and non-recursive CIC filters.

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This work presents a wideband low-distortion sigmadelta analog-to-digital converter (ADC) for Wireless Local Area Network (WLAN) standard. The proposed converter makes use of low-distortion swing suppression SDM architecture which is highly suitable for low oversampling ratios to attain high linearity over a wide bandwidth. The modulator employs a 2-2 cascaded sigma-delta modulator with feedforward path with a single-bit quantizer in the first stage and 4-bit in the second stage. The modulator is designed in TSMC 0.18um CMOS technology and operates at 1.8V supply voltage. Simulation results show that, a peak SNDR of 57dB and a spurious free dynamic range (SFDR) of 66dB is obtained for a 10MHz signal bandwidth, and an oversampling ratio of 8.

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The demand for new telecommunication services requiring higher capacities, data rates and different operating modes have motivated the development of new generation multi-standard wireless transceivers. In multistandard design, sigma-delta based ADC is one of the most popular choices. To this end, in this paper we present cascaded 2-2-2 reconfigurable sigma-delta modulator that can handle GSM, WCDMA and WLAN standards. The modulator makes use of a low-distortion swing suppression topology which is highly suitable for wide band applications. In GSM mode, only the first stage (2nd order Σ-Δ ADC) is used to achieve a peak SNDR of 88dB with oversampling ratio of 160 for a bandwidth of 200KHz and for WCDMA mode a 2-2 cascaded structure (4th order) is turned on with 1-bit in the first stage and 2-bit in the second stage to achieve 74 dB peak SNDR with over-sampling ratio of 16 for a bandwidth of 2MHz. Finally, a 2-2-2 cascaded MASH architecture with 4-bit in the last stage is proposed to achieve a peak SNDR of 58dB for WLAN for a bandwidth of 20MHz. The novelty lies in the fact that unused blocks of second and third stages can be made inactive to achieve low power consumption. The modulator is designed in TSMC 0.18um CMOS technology and operates at 1.8 supply voltage

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This work presents a triple-mode sigma-delta modulator for three wireless standards namely GSM/WCDMA and Bluetooth. A reconfigurable ADC has been used to meet the wide bandwidth and high dynamic range requirements of the multi-standard receivers with less power consumption. A highly linear sigma-delta ADC which has reduced sensitivity to circuit imperfections has been chosen in our design. This is particularly suitable for wide band applications where the oversampling ratio is low. Simulation results indicate that the modulator achieves a peak SNDR of 84/68/68 dB over a bandwidth of 0.2/3.84/1.5 MHz with an oversampling ratio 128/8/8 in GSM/WCDMA/Bluetooth modes respectively

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Over-sampling sigma-delta analogue-to-digital converters (ADCs) are one of the key building blocks of state of the art wireless transceivers. In the sigma-delta modulator design the scaling coefficients determine the overall signal-to-noise ratio. Therefore, selecting the optimum value of the coefficient is very important. To this end, this paper addresses the design of a fourthorder multi-bit sigma-delta modulator for Wireless Local Area Networks (WLAN) receiver with feed-forward path and the optimum coefficients are selected using genetic algorithm (GA)- based search method. In particular, the proposed converter makes use of low-distortion swing suppression SDM architecture which is highly suitable for low oversampling ratios to attain high linearity over a wide bandwidth. The focus of this paper is the identification of the best coefficients suitable for the proposed topology as well as the optimization of a set of system parameters in order to achieve the desired signal-to-noise ratio. GA-based search engine is a stochastic search method which can find the optimum solution within the given constraints.

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This paper presents a cascaded 2-2-2 reconfigurable sigma-delta modulator that can handle GSM, WCDMA and WLAN standards. The modulator makes use of a low-distortion swing suppression topology which is highly suitable for wide band applications. In GSM mode, only the first stage (2nd order Σ-Δ ADC) is turned on to achieve 88dB dynamic range with oversampling ratio of 160 for a bandwidth of 200KHz; in WCDMA mode a 2-2 cascaded structure (4th order) is turned on with 1-bit in the first stage and 2-bit in the second stage to achieve 74 dB dynamic range with oversampling ratio of 16 for a bandwidth of 2MHz and a 2-2-2 cascaded MASH architecture with a 4-bit in the last stage to achieve a dynamic range of 58dB for a bandwidth of 20MHz. The novelty lies in the fact that unused blocks of second and third stages can be switched off taking into considerations like power consumption. The modulator is designed in TSMC 0.18um CMOS technology and operates at 1.8 supply voltage.

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We develop an extension to the tactical planning model (TPM) for a job shop by the third author. The TPM is a discrete-time model in which all transitions occur at the start of each time period. The time period must be defined appropriately in order for the model to be meaningful. Each period must be short enough so that a job is unlikely to travel through more than one station in one period. At the same time, the time period needs to be long enough to justify the assumptions of continuous workflow and Markovian job movements. We build an extension to the TPM that overcomes this restriction of period sizing by permitting production control over shorter time intervals. We achieve this by deriving a continuous-time linear control rule for a single station. We then determine the first two moments of the production level and queue length for the workstation.

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Exercises, exams and solutions for a third year finance course.

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This work provides a framework for the approximation of a dynamic system of the form x˙=f(x)+g(x)u by dynamic recurrent neural network. This extends previous work in which approximate realisation of autonomous dynamic systems was proven. Given certain conditions, the first p output neural units of a dynamic n-dimensional neural model approximate at a desired proximity a p-dimensional dynamic system with n>p. The neural architecture studied is then successfully implemented in a nonlinear multivariable system identification case study.

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This paper derives exact discrete time representations for data generated by a continuous time autoregressive moving average (ARMA) system with mixed stock and flow data. The representations for systems comprised entirely of stocks or of flows are also given. In each case the discrete time representations are shown to be of ARMA form, the orders depending on those of the continuous time system. Three examples and applications are also provided, two of which concern the stationary ARMA(2, 1) model with stock variables (with applications to sunspot data and a short-term interest rate) and one concerning the nonstationary ARMA(2, 1) model with a flow variable (with an application to U.S. nondurable consumers’ expenditure). In all three examples the presence of an MA(1) component in the continuous time system has a dramatic impact on eradicating unaccounted-for serial correlation that is present in the discrete time version of the ARMA(2, 0) specification, even though the form of the discrete time model is ARMA(2, 1) for both models.

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Variational data assimilation in continuous time is revisited. The central techniques applied in this paper are in part adopted from the theory of optimal nonlinear control. Alternatively, the investigated approach can be considered as a continuous time generalization of what is known as weakly constrained four-dimensional variational assimilation (4D-Var) in the geosciences. The technique allows to assimilate trajectories in the case of partial observations and in the presence of model error. Several mathematical aspects of the approach are studied. Computationally, it amounts to solving a two-point boundary value problem. For imperfect models, the trade-off between small dynamical error (i.e. the trajectory obeys the model dynamics) and small observational error (i.e. the trajectory closely follows the observations) is investigated. This trade-off turns out to be trivial if the model is perfect. However, even in this situation, allowing for minute deviations from the perfect model is shown to have positive effects, namely to regularize the problem. The presented formalism is dynamical in character. No statistical assumptions on dynamical or observational noise are imposed.

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Data assimilation refers to the problem of finding trajectories of a prescribed dynamical model in such a way that the output of the model (usually some function of the model states) follows a given time series of observations. Typically though, these two requirements cannot both be met at the same time–tracking the observations is not possible without the trajectory deviating from the proposed model equations, while adherence to the model requires deviations from the observations. Thus, data assimilation faces a trade-off. In this contribution, the sensitivity of the data assimilation with respect to perturbations in the observations is identified as the parameter which controls the trade-off. A relation between the sensitivity and the out-of-sample error is established, which allows the latter to be calculated under operational conditions. A minimum out-of-sample error is proposed as a criterion to set an appropriate sensitivity and to settle the discussed trade-off. Two approaches to data assimilation are considered, namely variational data assimilation and Newtonian nudging, also known as synchronization. Numerical examples demonstrate the feasibility of the approach.