Sentence examples for that can sparsely from inspiring English sources

Dictionary learning aims to generate a compact dictionary that can sparsely represent the incoming signal with minimum error.

Sparse coding has been successfully applied to model local features, and to construct overcomplete dictionary that can sparsely represent the local features.

Consider the signal f=[σ1,…,σ N ] T with N=N x N y that can be sparsely represented by means of the transform matrix Ψ, which describes an N×N unitary basis such that f = Ψ H χ, (23).

A dictionary is learned either from the corrupted image or a high-quality set of images with the assumption that it can sparsely represent any natural image.

A compressible signal means that it can sparsely be represented in some basis, and can exactly be reconstructed only with a small set of random projections on an incoherent basis[8 10].

This paper examines networks with nodes that are sparsely connected that may have a hierarchical structure that can be exploited using parts of graph theory to develop a solution.

As discussed above in terms of read mapping, genetic differences between the isolates can only be identified if they are sparsely distributed and located close to conserved regions that can anchor the mapped reads.

Most of the deep sea is sparsely populated, its animals living on what settles down from above, but volcanic and other deep-sea vents emit gases that can be oxidized to provide energy.

We demonstrated that individual pyramidal cells are sparsely interconnected by thousands of excitatory synaptic connections that extend, largely undiminished, across the piriform cortex, forming a large excitatory network that can dominate the bulbar input.

Nowadays the forest is mainly composed by the species C. barbata that can be found in varying densities at depths of about 2 to 5 m. C. compressa is the only other species sparsely present, particularly at shallower depths.

From our experiments, it is shown that the proposed SNEP-based speaker adaptation method can sparsely adapt the SI model (only about 9%% of the total number of parameters) with no loss of phone recognition performance against MAP adaptation.