A Compressed Sensing Approach for Modeling the Super-Resolution Near-Field Structure Disc System With a Sparse Volterra Filter

Performance evaluation of decision feedback equalizers in fiber communication links

“…To alleviate the complexity issues inherently introduced in the electronic equalizers, sparsity induced equalizers are introduced. This task is accomplished resorting to sparse filtering techniques for the suppression of those terms in (1) that have a marginal contribution in the overall performance, resulting to a sparsified representation of the pertinent equalizer (see among [19][20][21] and the references therein). The resulted sparse representation, compared to the full terms (dense) design, is more tractable from an implementation point of view, since operators involving zero values can be omitted leading to large computational complexity savings.…”

Domain Bloom in Super-Resolution Near-Field Structure Read-Out Signals

“…( 2) reduces to a truncated second-order Volterra filter. 9,11,18,19) The linear and quadratic kernels consist of a combination of channel impulse response h k 's and for consistency parameter A. The quadratic terms produce a DC offset that depends on the data fa k g and second-order nonlinearities.…”

“…As widely known, unfortunately, super-RENS read-out samples are affected by a nonlinear and noncausal channel, which results in intersymbol interference. [6][7][8][9][10][11] To investigate these deleterious abnormalities for improving techniques that are being studied, a model that exactly describes these characteristics is an efficient tool for developing components of an associated high-density optical disc system. 12) It is known that some of these nonlinearities are caused by domain bloom or asymmetry.…”

“…Many studies regarding nonlinearities in optical recording systems, even though not mentioned superficially, focus on modeling the asymmetry in the read-out signal with various nonlinear models. 6,10,11,17) In this study, we investigate the effect of the domain bloom on the super-RENS read-out signal. For this, we employ the asymmetric symbol conversion scheme proposed in Ref.…”

A hierarchical alternative updated adaptive Volterra filter with pipelined architecture

“…Therefore, Volterra filters have been widely used in many fields such as nonlinear system identification [1][2][3], speech prediction [4,5], channel equalizer [6], acoustic echo cancellation [7], and image processing [8]. However, a major problem in the implementation of Volterra filters is their heavy computational complexity, which is caused by the large number of filter coefficients rising geometrically with the orders and memory depth (or delays).…”