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
If we want to sort many items, we have to store them in a 2D texture. To sort an entire 2D field, we understand each row of the field to be one bitonic sequence of the whole field. We therefore perform the same sorting operations for every row. The quads we have introduced prev...
But std::sort using quick sort algorithm. It's pick element and put lower element at begin and bigger element at end. Then recursive sort. So, if we will pick long vector it will be compared O(len(curr arr)) size. hmm, ok, my words are true until C++11 since C++11 it's using ...
Given a vector x¯∈Bn, denote by x¯R‾ the vector obtained from x¯ by reversing and complementing each bit. For example, 100R‾=110. Lemma 8 Let C be a comparator network on n channels and CR be its reflection. Then x¯∈outputs(C) if and only if x¯R‾∈outputs...
int cmp(const PAIR& x, const PAIR& y) { return x.second < y.second; } void OutputMessage() { map<string, int>::const_iterator map_it = result.begin(); vector<PAIR> vecpair; for(map<string, int>::iterator curr = result.begin(); curr != result.end(); ++curr) ...
For each layer in the sorting network, we can split all of the pairwise comparison-and-swaps into left-hand and right-hand sides. We can any write function that selects the relevant elements of the vector as a multiply with a binary matrix. ...
where our dependent variable is the relative income of out-migrant households and is defined for each pair of home and destination locations (h,d) as the ratio of the average income of households moving fromh(where they were living in yeart−1) todto the average income of households stayi...
Multiple criteria sorting methods assign objects into ordered categories while objects are characterized by a vector of n attributes values. Categories are
linear in n, and it can be performed in-place, meaning that the data points pi can be overwritten with the mean-centered values xi if memory consumption is an issue. The second step consists of computing the first principal component v1∈Rd, i.e., the vector along which the data {xi...
In contrast to the MV, our proposed WDV focuses on the battery similarities between the recycler and each client by measuring the pairwise distance. We aim to assign fewer weightings to the clients with biased data distributions (equivalently, higher heterogeneity), whose batteries are of higher...