QR algorithm and array architectures for multichannel adaptive least squares lattice filters

An algorithm and a set of array architectures that implement and multichannel adaptive least squares lattice filter are presented. The algorithm is based on QR decomposition and provides both a numerically sound and regularly structured set of recursions. For m channels and p filter taps, O(pm²) computations are required at each sample update. Several array architectures are presented to illustrate the space-time tradeoffs available. These range from an array of p processing elements (PEs) that compute a sample update in O(m²) time to an array of O(pm²) PEs that computes the update in constant time. The in-between arrays of O(m), O(m²), or O(pm) PEs are also outlined