tailieunhanh - Lập Trình C# all Chap "NUMERICAL RECIPES IN C" part 123

Tham khảo tài liệu 'lập trình c# all chap "numerical recipes in c" part 123', công nghệ thông tin phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 564 Chapter 13. Fourier and Spectral Applications for specific situations and arm themselves with a variety of other tricks. We suggest that you do likewise as your projects demand. CITED REFERENCES AND FURTHER READING Hamming . 1983 Digital Filters 2nd ed. Englewood Cliffs NJ Prentice-Hall . Antoniou A. 1979 Digital Filters Analysis and Design New York McGraw-Hill . Parks . and Burrus . 1987 Digital Filter Design New York Wiley . Oppenheim . and Schafer . 1989 Discrete-Time Signal Processing Englewood Cliffs NJ Prentice-Hall . Rice . 1964 The Approximation of Functions Reading MA Addison-Wesley also 1969 op. cit. Vol. 2. Rabiner . and Gold B. 1975 TheoryandApplication of Digital SignalProcessing Englewood Cliffs NJ Prentice-Hall . Linear Prediction and Linear Predictive Coding We begin with a very general formulation that will allow us to make connections to various special cases. Let y a be a set of measured values for some underlying set of true values of a quantity y denoted ya related to these true values by the addition of random noise y a ya na compare equation with a somewhat different notation . Our use of a Greek subscript to index the members of the set is meant to indicate that the data points are not necessarily equally spaced along a line or even ordered they might be random points in three-dimensional space for example. Now suppose we want to construct the best estimate of the true value of some particular point y as a linear combination of the known noisy values. Writing y 2 d ay a x we want to find coefficients d a that minimize in some way the discrepancy x . The coefficients d a have a star subscript to indicate that they depend on the choice of point y . Later we might want to let y be one of the existing ya s. In that case our problem becomes one of optimal filtering or estimation closely related to the discussion in . On the other hand we might want y to be a completely new point. In that case

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