So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Human biochemical genetics

A digital computer is generally believed to be an efficient universal computing device; that is, it is believed able to simulate any physical computing device with an increase in computation time by at most a polynomial factor. This may not be true when quantum mechanics is taken into consideration. This paper considers factoring integers and finding discrete logarithms, two problems which are generally thought to be hard on a classical computer and which have been used as the basis of several proposed cryptosystems. Efficient randomized algorithms are given for these two problems on a hypothetical quantum computer. These algorithms take a number of steps polynomial in the input size, e.g., the number of digits of the integer to be factored.

Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer

A summary of many of the new techniques developed in the last two decades for spectrum analysis of discrete time series is presented in this tutorial. An examination of the underlying time series model assumed by each technique serves as the common basis for understanding the differences among the various spectrum analysis approaches. Techniques discussed include the classical periodogram, classical Blackman-Tukey, autoregressive (maximum entropy), moving average, autotegressive-moving average, maximum likelihood, Prony, and Pisarenko methods. A summary table in the text provides a concise overview for all methods, including key references and appropriate equations for computation of each spectral estimate.

Spectrum analysis&#8212;A modern perspective

A digital computer is generally believed to be an efficient universal computing device; that is, it is believed to be able to simulate any physical computing device with an increase in computation time by at most a polynomial factor. This may not be true when quantum mechanics is taken into consideration. This paper considers factoring integers and finding discrete logarithms, two problems that are generally thought to be hard on classical computers and that have been used as the basis of several proposed cryptosystems. Efficient randomized algorithms are given for these two problems on a hypothetical quantum computer. These algorithms take a number of steps polynomial in the input size, for example, the number of digits of the integer to be factored.

/pdf/polynomial-time-algorithms-for-prime-factorization-and-rtdp7rr21z.pdf

Digital watermarking is a key ingredient to copyright protection. It provides a solution to illegal copying of digital material and has many other useful applications such as broadcast monitoring and the recording of electronic transactions. Now, for the first time, there is a book that focuses exclusively on this exciting technology. Digital Watermarking covers the crucial research findings in the field: it explains the principles underlying digital watermarking technologies, describes the requirements that have given rise to them, and discusses the diverse ends to which these technologies are being applied. As a result, additional groundwork is laid for future developments in this field, helping the reader understand and anticipate new approaches and applications.

Digital Watermarking

A method is presented for computing an orthonormal set of eigenvectors for the discrete Fourier transform (DFT). The technique is based on a detailed analysis of the eigenstructure of a special matrix which commutes with the DFT. It is also shown how fractional powers of the DFT can be efficiently computed, and possible applications to multiplexing and transform coding are suggested.

/pdf/eigenvectors-and-functions-of-the-discrete-fourier-transform-2q9wnfgbp2.pdf

Eigenvectors and functions of the discrete Fourier transform

In a system for compressing video data, the degree of global motion between a plurality of successive frames is determined for use in designating and spacing reference frames, relative to the global motion exceeding predetermined thresholds or levels of motion between certain ones of the frames.

Method and apparatus for video data compression using temporally adaptive motion interpolation

https://www.cs.princeton.edu/courses/archive/fall04/cos576/papers/vergis_steiglitz_dickinson86.pdf

The complexity of analog computation

An adaptive watermarking technique is introduced in this work. A regional perceptual classifier is employed to assign a noise sensitivity index to each region. The watermark is inserted in the original image according to this index by using block DCT. The detection of the watermark is designed to achieve a desired false alarm probability.

Adaptive watermarking in the DCT domain

An algorithm for the solution of the linear equations for the "covariance method" of linear prediction is stated and proved. The algorithm requires only O(p2) arithmetic operations, and in form resembles the Levinson algorithm for solution of the linear equations for the "correlation method" of linear prediction. The structural properties of the problem and its solution are emphasized in the analysis presented.

Bradley W. Dickinson

Papers

Eigenvectors and functions of the discrete Fourier transform

Method and apparatus for video data compression using temporally adaptive motion interpolation

The complexity of analog computation

Adaptive watermarking in the DCT domain

Efficient solution of covariance equations for linear prediction