Blind adaptive decision feedback equalization.

Kurban, Esra


Blind channel identification methods and channel order estimation
Tuncer, Temel Engin (2006-04-19)
n this paper, we consider three blind channel estimation methods. Cross-relation (CR), subspace (SS) and least squares smoothing (J-LSS) methods are compared for single-input multi-output (SIMO) systems. In contrast to the previous works, we evaluate the practical MSE performances of these methods for short data lengths and random channels when the number of channels is greater than two. Some previously unknown characteristics of these methods are presented. A novel method for blind channel order estimation...
Blind equalizaiton and carrier phase tracking in two-dimensional data communication systems.
Candaner, H. Füsun; Department of Electrical Engineering (1985)
Sequential decision making problems in normed linear spaces.
Çapar, Ulug; Körezlioğlu, Hayri; Department of Mathematics (1972)
Blind Deinterleaving of Signals in Time Series with Self-Attention Based Soft Min-Cost Flow Learning
Can, Oğul; Gürbüz, Yeti Ziya; Yildirim, Berkin; Alatan, Abdullah Aydın (2021-01-01)
We propose an end-to-end learning approach to address deinterleaving of patterns in time series, in particular, radar signals. We link signal clustering problem to min-cost flow as an equivalent problem once the proper costs exist. We formulate a bi-level optimization problem involving min-cost flow as a sub-problem to learn such costs from the supervised training data. We then approximate the lower level optimization problem by self-attention based neural networks and provide a trainable framework that clu...
Feedback Motion Planning For a Dynamic Car Model via Random Sequential Composition
Özcan, Melih; Ankaralı, Mustafa Mert (2019-01-01)
Autonomous cars and car-like robots have gained huge popularity recently due to the recent advancements in technology and AI industry. Motion and path planning is one of the most fundamental problems for such systems. In the literature, kinematic models are widely adopted for planning and control for these type of robots due to their simplicity (control and analysis) and fewer computational requirements. Though, applicability of kinematic models are limited to very low speeds or some specific cases, which c...
Citation Formats
E. Kurban, “Blind adaptive decision feedback equalization.,” Middle East Technical University, 2002.