A new way of analyzing grids of numbers known as matrices could improve signal-processing applications and data-compression schemes.
Among the most common tools in electrical engineering and computer science are rectangular grids of numbers known as matrices. The numbers in a matrix can represent data: The rows, for instance, could represent temperature, air pressure and humidity, and the columns could represent different locations where those three measurements were taken. But matrices can also represent mathematical equations. If the expressions t + 2p + 3h and 4t + 5p + 6h described two different mathematical operations involving temperature, pressure and humidity measurements, they could be represented as a matrix with two rows, [1 2 3] and [4 5 6]. Multiplying the two matrices together means performing both mathematical operations on every column of the data matrix and entering the results in a new matrix. In many time-sensitive engineering applications, multiplying matrices can give quick but good approximations of much more complicated calculations.