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    Whimsical Girls : Fun Inspiration and Instant Creative Gratification

    Reclaim your creativity with this one-of-a-kind workbook of fabulous females to personalize!It’s perfect for coloring enthusiasts and mixed-media artists.  This is not your typical coloring book. Created by celebrated artist Jane Davenport, and dedicated solely to images of women, Whimsical Girls is bursting with Jane’s signature-style figures, faces, and fanciful drawings to color and customize.The unusual combination of four types of high-quality paper—coloring, marker, watercolor, and kraft paper—encourages users to experiment with a variety of mediums and techniques.Inspirational examples and prompts help allay budding artists’ nervousness, while bonus stickers and brilliantly hued collage paper—to cut or tear and glue to the pages—provide added fuel for creativity!

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  • Parameter Hierarchies and Universal Grammar
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    This book develops a minimalist approach to cross-linguistic morphosyntactic variation.Ian Roberts argues that the essential insight of the principles-and-parameters approach to variation can be maintained - albeit in a somewhat different guise - in the context of the minimalist programme for linguistic theory.The central idea is to organize the parameters of Universal Grammar (UG) into hierarchies that define the ways in which properties of individually variant categories and features may act in concert.A further leading idea, which is consistent with the overall goal of the minimalist programme to reduce the content of UG, is that the parameter hierarchies are not directly determined by UG, and are instead emergent properties stemming from the interaction of the three factors in language design.Cross-linguistic variation in word order, null subjects, incorporation, verb-movement, case/alignment, wh-movement, and negation are all analysed in the light of this approach.This book represents a significant new contribution to the formal study of cross-linguistic morphosyntactic variation on both the empirical and theoretical levels, and will appeal to researchers and students in all areas of theoretical linguistics and comparative syntax.

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  • Stationary Processes and Discrete Parameter Markov Processes
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    This textbook explores two distinct stochastic processes that evolve at random: weakly stationary processes and discrete parameter Markov processes.Building from simple examples, the authors focus on developing context and intuition before formalizing the theory of each topic.This inviting approach illuminates the key ideas and computations in the proofs, forming an ideal basis for further study. After recapping the essentials from Fourier analysis, the book begins with an introduction to the spectral representation of a stationary process.Topics in ergodic theory follow, including Birkhoff's Ergodic Theorem and an introduction to dynamical systems.From here, the Markov property is assumed and the theory of discrete parameter Markov processes is explored on a general state space.Chapters cover a variety of topics, including birth-death chains, hitting probabilities and absorption, the representation of Markov processes as iterates of random maps, and large deviation theory for Markov processes.A chapter on geometric rates of convergence to equilibrium includes a splitting condition that captures the recurrence structure of certain iterated maps in a novel way.A selection of special topics concludes the book, including applications of large deviation theory, the FKG inequalities, coupling methods, and the Kalman filter. Featuring many short chapters and a modular design, this textbook offers an in-depth study of stationary and discrete-time Markov processes.Students and instructors alike will appreciate the accessible, example-driven approach and engaging exercises throughout.A single, graduate-level course in probability is assumed.

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  • 3D Rotations : Parameter Computation and Lie Algebra based Optimization
    3D Rotations : Parameter Computation and Lie Algebra based Optimization

    3D rotation analysis is widely encountered in everyday problems thanks to the development of computers.Sensing 3D using cameras and sensors, analyzing and modeling 3D for computer vision and computer graphics, and controlling and simulating robot motion all require 3D rotation computation.This book focuses on the computational analysis of 3D rotation, rather than classical motion analysis.It regards noise as random variables and models their probability distributions.It also pursues statistically optimal computation for maximizing the expected accuracy, as is typical of nonlinear optimization.All concepts are illustrated using computer vision applications as examples. Mathematically, the set of all 3D rotations forms a group denoted by SO(3).Exploiting this group property, we obtain an optimal solution analytical or numerically, depending on the problem.Our numerical scheme, which we call the "Lie algebra method," is based on the Lie group structure of SO(3). This book also proposes computing projects for readers who want to code the theories presented in this book, describing necessary 3D simulation setting as well as providing real GPS 3D measurement data.To help readers not very familiar with abstract mathematics, a brief overview of quaternion algebra, matrix analysis, Lie groups, and Lie algebras is provided as Appendix at the end of the volume.

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  • 3D Rotations : Parameter Computation and Lie Algebra based Optimization
    3D Rotations : Parameter Computation and Lie Algebra based Optimization

    3D rotation analysis is widely encountered in everyday problems thanks to the development of computers.Sensing 3D using cameras and sensors, analyzing and modeling 3D for computer vision and computer graphics, and controlling and simulating robot motion all require 3D rotation computation.This book focuses on the computational analysis of 3D rotation, rather than classical motion analysis.It regards noise as random variables and models their probability distributions.It also pursues statistically optimal computation for maximizing the expected accuracy, as is typical of nonlinear optimization.All concepts are illustrated using computer vision applications as examples. Mathematically, the set of all 3D rotations forms a group denoted by SO(3).Exploiting this group property, we obtain an optimal solution analytical or numerically, depending on the problem.Our numerical scheme, which we call the "Lie algebra method," is based on the Lie group structure of SO(3). This book also proposes computing projects for readers who want to code the theories presented in this book, describing necessary 3D simulation setting as well as providing real GPS 3D measurement data.To help readers not very familiar with abstract mathematics, a brief overview of quaternion algebra, matrix analysis, Lie groups, and Lie algebras is provided as Appendix at the end of the volume.

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  • Parameter Estimation and Adaptive Control for Nonlinear Servo Systems
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    Parameter Estimation and Adaptive Control for Nonlinear Servo Systems presents the latest advances in observer-based control design, focusing on adaptive control for nonlinear systems such as adaptive neural network control, adaptive parameter estimation, and system identification.This book offers an array of new, real-world applications in the field.Written by eminent scientists in the field of control theory, this book covers the latest advances in observer-based control design and provides fundamentals, algorithms, and key applications in the fields of power systems, robotics and mechatronics, flight, and automotive systems.

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Similar search terms for Parameter:


  • What is parameter 4?

    Parameter 4 is the fourth variable or value in a function or method. It is used to pass additional information or data to the function in order to customize its behavior or output. Parameter 4 can be any type of data, such as a number, string, array, or object, depending on the requirements of the function being called. It is important to correctly define and pass parameter 4 to ensure the function operates as intended.

  • What is parameter 3?

    Parameter 3 is the third variable or value that is passed to a function or method. It is used to provide additional information or data to the function in order to perform a specific task or calculation. The function will use parameter 3 along with other parameters to execute its functionality and return a result. It is important to pass the correct data type and value to parameter 3 to ensure the function works as intended.

  • What is a parameter comparison?

    A parameter comparison is the process of evaluating and analyzing different parameters or variables to determine their similarities and differences. This comparison helps in understanding the relationships between these parameters and their impact on a system or process. By comparing parameters, researchers can identify patterns, trends, and correlations that can provide valuable insights for decision-making and problem-solving.

  • What is a real parameter?

    A real parameter is a constant value that is used in mathematical equations or models. It is a fixed value that does not change during the course of the analysis. Real parameters are typically used to represent physical quantities or characteristics of a system, and they help define the behavior or properties of the system being studied. Examples of real parameters include coefficients in equations, physical constants like the speed of light, or other fixed values that influence the outcome of a mathematical model.

  • What is the parameter form?

    The parameter form is a way to represent a line or a plane in three-dimensional space using parameters. For a line, the parameter form is typically written as a vector equation, where a point on the line is given by a position vector plus a parameter times a direction vector. For a plane, the parameter form is written as a vector equation, where a point on the plane is given by a position vector plus two parameters times two direction vectors. The parameters allow for flexibility in describing the position of points on the line or plane.

  • What is the parameter 5?

    The parameter 5 is a value that is used to define or set a specific condition or limit within a system or function. It can represent a fixed value, a boundary, or a constraint that affects the behavior or outcome of a process. In mathematical terms, it can be a constant that is used in an equation or formula to represent a specific quantity. In programming, it can be a variable that is passed into a function to customize its behavior.

  • How is the parameter a0 determined?

    The parameter a0 is determined by setting the input variable to zero in the equation or function being analyzed. This means that a0 represents the value of the function at the origin or when the input is zero. By evaluating the function at this specific point, we can isolate and determine the value of a0.

  • What is the parameter task 2?

    Parameter task 2 refers to a specific task or objective that is defined within a larger project or process. It is a set of instructions or requirements that need to be completed in order to achieve a certain goal. Task 2 may include specific guidelines, deadlines, and deliverables that need to be met in order to move the project forward. It is an essential component of project management and helps to ensure that all necessary steps are taken to achieve the desired outcome.

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