Determination of nonlinear genetic architecture using compressed sensing
نویسندگان
چکیده
منابع مشابه
Determination of nonlinear genetic architecture using compressed sensing
BACKGROUND One of the fundamental problems of modern genomics is to extract the genetic architecture of a complex trait from a data set of individual genotypes and trait values. Establishing this important connection between genotype and phenotype is complicated by the large number of candidate genes, the potentially large number of causal loci, and the likely presence of some nonlinear interac...
متن کاملFrames for compressed sensing using coherence
We give some new results on sparse signal recovery in the presence of noise, for weighted spaces. Traditionally, were used dictionaries that have the norm equal to 1, but, for random dictionaries this condition is rarely satised. Moreover, we give better estimations then the ones given recently by Cai, Wang and Xu.
متن کاملCompressed Sensing with Nonlinear Observations
Compressed sensing is a recently developed signal acquisition technique. In contrast to traditional sampling methods, significantly fewer samples are required whenever the signals admit a sparse representation. Crucially, sampling methods can be constructed that allow the reconstruction of sparse signals from a small number of measurements using efficient algorithms. We have recently generalise...
متن کاملautomatic verification of authentication protocols using genetic programming
implicit and unobserved errors and vulnerabilities issues usually arise in cryptographic protocols and especially in authentication protocols. this may enable an attacker to make serious damages to the desired system, such as having the access to or changing secret documents, interfering in bank transactions, having access to users’ accounts, or may be having the control all over the syste...
15 صفحه اولCompressed Sensing Image Recovery Using Adaptive Nonlinear Filtering
Compressed sensing is a technique that consists providing efficient, stable and fast recovery algorithms which, in a few seconds, evaluate a good approximation of a compressible image from highly incomplete and noisy samples. In this paper, using adaptive nonlinear filtering strategies in an iterative framework can be avoiding the recovery image problem. In this technique has more efficient, st...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: GigaScience
سال: 2015
ISSN: 2047-217X
DOI: 10.1186/s13742-015-0081-6