A comprehensive design framework is proposed for optimizing sparse MIMO (multiple-input, multiple-output) arrays to enhance multi-target detection. The framework emphasizes efficient utilization of antenna resources, including strategies for minimizing inter-element mutual coupling and exploring alternative grid-based sparse array (GBSA) configurations by efficiently separating interacting elements. Alternative strategies are explored to enhance angular beamforming metrics, including beamwidth (BW), peak-to-sidelobe ratio (PSLR), and grating lobe limited field of view.
View Article and Find Full Text PDFAttending to a manipulable object evokes a mental representation of hand actions associated with the object's form and function. In one view, these representations are sufficiently abstract that their competing influence on an unrelated action is confined to the planning stages of movement and does not affect its on-line control. Alternatively, an object may evoke action representations that affect the entire trajectory of an unrelated grasping action.
View Article and Find Full Text PDFObjective: To evaluate the effectiveness of a new method of using Independent Component Analysis (ICA) and k-means clustering to increase the signal-to-noise ratio of Event-Related Potential (ERP) measurements while permitting standard statistical comparisons to be made despite the inter-subject variations characteristic of ICA.
Methods: Per-subject ICA results were used to create a channel pool, with unequal weights, that could be applied consistently across subjects. Signals derived from this and other pooling schemes, and from unpooled electrodes, were subjected to identical statistical analysis of the N170 own-face effect in a Joe/No Joe face recognition paradigm wherein participants monitored for a target face (Joe) presented amongst other unfamiliar faces and their own face.