Spike sorting is the computational process of extracting the firing times of single neurons from recordings of local electrical fields. This is an important but hard problem in neuroscience, made complicated by the nonstationarity of the recordings and the dense overlap in electrical fields between nea...
1. A computerized method of sorting irregular objects, comprising: receiving a representative set of irregular objects comprising at least two types of user-specified qualities; receiving at least two types of measured data for the representative set of irregular objects; generating at least one of ...
Answer to: What would happen to the time complexity (Big-O) of the methods in an array implementation of a stack if the top of the stack were at...
Spike sorting is the computational process of extracting the firing times of single neurons from recordings of local electrical fields. This is an important but hard problem in neuroscience, made complicated by the nonstationarity of the recordings and t
During animal development, embryos undergo complex morphological changes over time. Differences in developmental tempo between species are emerging as principal drivers of evolutionary novelty, but accurate description of these processes is very challeng
Suppose we have yearly data of returns. 252 returns in dollars in total. Let us take c=95%. So, the confidence level is c=95%. The negative dollar returns are regarded as losses. First, we compute the portfolio values based on returns by (2.1.1). Sorting the returns in ascending ord...
1. A method for performing structural joins of two element sets of a tree-structured document, wherein one of the two element sets is an ancestor element set and the other of the two element sets is a descendant element set, and further wherein each element is represented as an interval ...
In this paper, we present an application of soft computing methods for the problem of WiMax Network Planning on 3D Geographical Information Systems (3D GIS) that optimizes both performance of the network (Coverage and Quality-of-Service) and investment costs (the number of base stations and sect...
This entry presents an overview of cluster analysis, the cluster and clustermat commands (also see [MV] clustermat), as well as Stata's cluster-analysis management tools. The hierarchical clustering methods may be applied to the data by using the cluster command or to a user-supplied ...
For sparse methods like LASSO, it has been previously shown that using self-reported ancestry performs similarly to principal component based clustering when based on AUC and correlation metrics11. Nonetheless, after sorting on self-reported ancestry, we perform an additional regression on the top 20...