Suppose we have a large number of symbol sequences emitted from an HMM that has a particular transition probability ai!j! = 0 for some single value of i# and j#. We use such sequences to train a new HMM, one that happens also to start with its ai!j! = 0. Prove that this parameter will remain 0 throughout training by the Forward-backward algorithm. In other words, if the topology of the trained model (pattern of non-zero connections) matches that of the generating HMM, it will remain so after training.

These factors limit the ability to attach files to e-mail messages. location of sender recipient's ability to open file size of file type of operating system used

Create a string list. 2. use console.readline() to collect values of firstname, lastname, street, city, state, zip, save them to list. 3. write a simple linq statement, call method uppercasewords() to change first letter to uppercase. 4. create a foreach statment to display the information. public static string uppercasewords(string value) { char[] array = value.tochararray(); if (array.length > = 1) { if (char.islower(array[0])) { array[0] = char.toupper(array[0]); } } for (int i = 1; i < array.length; i++) { if (array[i - 1] == ' ') { if (char.islower(array[i])) { array[i] = char.toupper(array[i]); } } } return new string(array);

Which of the following types of software is most applicable to the promotion of new products through advertising? a.databases b. spreadsheets c. web design programs d. word processing tools