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Formula

  • DTMF的原理和算法公式

    ·詳細(xì)說明:本文章說明一個可以快速識別和產(chǎn)生DTMF的DSP算法原理!里面詳細(xì)說明了DTMF的原理和算法公式- This article explained may fast distinguish and have the DTMF DSP algorithm principle! Inside specify DTMF principle and algorithm Formula

    標(biāo)簽: DTMF 算法

    上傳時間: 2013-04-24

    上傳用戶:lw852826

  • 基于MASON公式的多功能二階通用濾波器設(shè)計

    基于通用集成運算放大器,利用MASON公式設(shè)計了一個多功能二階通用濾波器,能同時或分別實現(xiàn)低通、高通和帶通濾波,也能設(shè)計成一個正交振蕩器。電路的極點頻率和品質(zhì)因數(shù)能夠獨立、精確地調(diào)節(jié)。電路使用4個集成運放、2個電容和11個電阻,所有集成運放的反相端虛地。利用計算機(jī)仿真電路的通用濾波功能、極點頻率和品質(zhì)因數(shù)的獨立控制和正交正弦振蕩,從而證明該濾波器正確有效。 Abstract:  A new multifunctional second-order filter based on OPs was presented by MASON Formula. Functions, such as high-pass, band-pass, low-pass filtering, can be realized respectively and simultaneously, and can become a quadrature oscillator by modifying resistance ratio. Its pole angular frequency and quality factor can be tuned accurately and independently. The circuit presented contains four OPs, two capacitors, and eleven resistances, and inverting input of all OPs is virtual ground. Its general filtering, the independent control of pole frequency and quality factor and quadrature sinusoidal oscillation were simulated by computer, and the result shows that the presented circuit is valid and effective.

    標(biāo)簽: MASON 多功能 二階 濾波器設(shè)計

    上傳時間: 2013-10-09

    上傳用戶:13788529953

  • In this paper, we consider the problem of filtering in relational hidden Markov models. We present

    In this paper, we consider the problem of filtering in relational hidden Markov models. We present a compact representation for such models and an associated logical particle filtering algorithm. Each particle contains a logical Formula that describes a set of states. The algorithm updates the Formulae as new observations are received. Since a single particle tracks many states, this filter can be more accurate than a traditional particle filter in high dimensional state spaces, as we demonstrate in experiments.

    標(biāo)簽: relational filtering consider problem

    上傳時間: 2016-01-02

    上傳用戶:海陸空653

  • Computes BER v EbNo curve for convolutional encoding / soft decision Viterbi decoding scheme assum

    Computes BER v EbNo curve for convolutional encoding / soft decision Viterbi decoding scheme assuming BPSK. Brute force Monte Carlo approach is unsatisfactory (takes too long) to find the BER curve. The computation uses a quasi-analytic (QA) technique that relies on the estimation (approximate one) of the information-bits Weight Enumerating Function (WEF) using A simulation of the convolutional encoder. Once the WEF is estimated, the analytic Formula for the BER is used.

    標(biāo)簽: convolutional Computes encoding decision

    上傳時間: 2013-12-24

    上傳用戶:咔樂塢

  • A large body of computer-aided techniques has been developed in recent years to assist in the proce

    A large body of computer-aided techniques has been developed in recent years to assist in the process of modeling, analyzing, and designing communication systems . These computer-aided techniques fall into two categories: Formula-based approaches, where the computer is used to evaluate complex Formulas, and simulation-based approaches, where the computer is used to simulate the waveforms or signals that flow through the system. The second approach, which involves “waveform”-level simulation (and often incorporates analytical techniques), is the subject of this book. Since performance evaluation and trade off studies are the central issues in the analysis and design of communication systems, we will focus on the use of simulation for evaluating the performance of analog and digital communication systems with the emphasis on digitalcommunication systems.

    標(biāo)簽: computer-aided techniques developed assist

    上傳時間: 2014-01-01

    上傳用戶:541657925

  • Stochastic Geometry and Wireless Networks Volume I

    Part I provides a compact survey on classical stochastic geometry models. The basic models defined in this part will be used and extended throughout the whole monograph, and in particular to SINR based models. Note however that these classical stochastic models can be used in a variety of contexts which go far beyond the modeling of wireless networks. Chapter 1 reviews the definition and basic properties of Poisson point processes in Euclidean space. We review key operations on Poisson point processes (thinning, superposition, displacement) as well as key Formulas like Campbell’s Formula. Chapter 2 is focused on properties of the spatial shot-noise process: its continuity properties, its Laplace transform, its moments etc. Both additive and max shot-noise processes are studied. Chapter 3 bears on coverage processes, and in particular on the Boolean model. Its basic coverage characteristics are reviewed. We also give a brief account of its percolation properties. Chapter 4 studies random tessellations; the main focus is on Poisson–Voronoi tessellations and cells. We also discuss various random objects associated with bivariate point processes such as the set of points of the first point process that fall in a Voronoi cell w.r.t. the second point process.

    標(biāo)簽: Stochastic Geometry Networks Wireless Volume and

    上傳時間: 2020-06-01

    上傳用戶:shancjb

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