Showing 2 open source projects for "stream"

View related business solutions
  • $300 Free Credits for Your Google Cloud Projects Icon
    $300 Free Credits for Your Google Cloud Projects

    Start building on Google Cloud with $300 in free credits. No commitment, no credit card required until you're ready to scale.

    Launch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
    Start Free Trial
  • Our Free Plans just got better! | Auth0 Icon
    Our Free Plans just got better! | Auth0

    With up to 25k MAUs and unlimited Okta connections, our Free Plan lets you focus on what you do best—building great apps.

    You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
    Try free now
  • 1

    smooth

    Wavelet smoothing in a data stream

    It is often necessary to smooth high frequency fluctuations out of data streams sequenced by time, position, etc. The 'smooth' utility applies such smoothing using the wavelet algorithm. This implementation of wavelet smoothing was optimized for use in a data stream. It was adapted from HMMSeg Wavelet.Java by Thomas E. Wilson, University of Michigan. HMMSeg Wavelet.Java was written by Andrew Hemmaplardh, University of Washington. http://noble.gs.washington.edu/proj/hmmseg/ Unsupervised segmentation of continuous genomic data, Bioinformatics 2007 23:1424-1426 See the above references for a more thorough description of the principles behind wavelet smoothing.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2

    segment

    Solve the Viterbi algorithm in a data stream

    It is often necessary to assign a series of discrete values to continuosly variable data sequenced by time, position, etc., thereby parsing the data into fewer and larger segments of variable width. The 'segment' utility takes an input data stream as a Hidden Markov Model and applies the Viterbi algorithm to find the most likely segmentation path through the data.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
Auth0 Logo