Essays about: "matlab monte carlo"
Showing result 1 - 5 of 25 essays containing the words matlab monte carlo.
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1. Power Estimation Tool for Digital Front-End 5G Radio ASIC
University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskapAbstract : Application Specific Integrated Circuits (ASICs) are critical to delivering on 5G’s promises of high speed, low latency, and expanded capacity. Digital Front-End (DFE) ASICs are particularly important components because they enhance crucial signal processing activities. READ MORE
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2. Backscatter Communications for 6G
University essay from Lunds universitet/Institutionen för elektro- och informationsteknikAbstract : The success of future Internet of Things (IoT) depends on, among the other things, developing energy-effcient communication techniques that can enable information exchange among billions of IoT devices with ultra-low/zero power consumption requirements. Ambient backscatter communications is an emerging technology, which utilizes the ambient Radio Frequency (RF) signal as the carrier to reduce the form-factor, and the battery requirements of low-cost small sensor type communication devices. READ MORE
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3. Importance Sampling in Wireless Communication Systems with Ultra-Low Error Rates
University essay from Lunds universitet/Institutionen för elektro- och informationsteknikAbstract : Simulation mimics the behaviour of real world processes or the system over time. It helps us to understand the impact of modification and the effect of introducing various interventions to a system. READ MORE
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4. Option pricing under Black-Scholes model using stochastic Runge-Kutta method.
University essay from Mälardalens högskola/Akademin för utbildning, kultur och kommunikationAbstract : The purpose of this paper is solving the European option pricing problem under the Black–Scholes model. Our approach is to use the so-called stochastic Runge–Kutta (SRK) numericalscheme to find the corresponding expectation of the functional to the stochastic differentialequation under the Black–Scholes model. READ MORE
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5. Particle-Based Online Bayesian Learning of Static Parameters with Application to Mixture Models
University essay from KTH/Matematisk statistikAbstract : This thesis investigates the possibility of using Sequential Monte Carlo methods (SMC) to create an online algorithm to infer properties from a dataset, such as unknown model parameters. Statistical inference from data streams tends to be difficult, and this is particularly the case for parametric models, which will be the focus of this paper. READ MORE