A fast and accurate non-iterative direction-of-arrival (DOA) estimation algorithm for multiple targets in additive white Gaussian noise is devised in this paper. The proposed estimator makes use of the two highest magnitudes discrete Fourier transform (DFT) coefficients of the input data and two of their associated neighboring bins, resulting in a deterministic complexity of ${\mathcal {O}}(N(1+\log (N)))$ with $N$ being the number of sensors. The bias and mean squares error of the DOA estimates are analyzed. The simulation results are presented to validate the correctness of theoretical derivation and demonstrate the superiority of the devised estimator over several conventional DOA estimators.

The theory of perfect reconstruction (PR) quadrature mirror filter (QMF) banks is used to analyze the general class of modulated filter banks (MFBs). It is found that there is an inherent tradeoff between the constraints imposed on the prototype and the modulation matrix to achieve PR. The authors propose a set of constraints on the modulation to achieve PR while retaining the desirable power complementary conditions on the polyphase components. The prototype filter can then be designed using the two-channel lossless lattice. It is surprising that the complete solution to this set of constraints is generated by the set of unitary matrices. This greatly increases the possible choices of modulation in the design of finite-impulse-response PR QMF banks. The usefulness of the proposed approach is demonstrated by deriving several existing MFBs, such as the extended lapped transform, as special cases of the unitary class of solution.

This paper reviews the implementation of fractal based image interpolation, the associated visual artifacts of the interpolated images, and various techniques, including novel contributions, that alleviate these awkward visual artifacts to achieve visually pleasant interpolated image. The fractal interpolation methods considered in this paper are based on the plain Iterative Function System (IFS) in spatial domain without additional transformation, where we believe that the benefits of additional transformation can be added onto the presented study without complication. Simulation results are presented to demonstrate the discussed techniques, together with the pros and cons of each techniques. Finally, a novel spatial domain interleave layer has been proposed to add to the IFS image system for improving the performance of the system from image zooming to interpolation with the preservation of the pixel intensity from the original low resolution image.