Matlab Algorithm The algorithm comprises the following functions:
• Startup Identification This function is used to find the startingPointIndex. To determine the startingPointIndex: 1. There must be at least 30-minutes worth of raw measurements to normalise all the readings using the 6th reading 2. Calculate the consecutive differences of the normalised readings 3. The startingPointIndex represents the index of the reading at which the two consecutive differences are >= 0.01
• Detrending The raw measurements may contain a trend. A trend is a continued increase or decrease over time. The available readings until the startingPointIndex are used to model the trend and remove it from the data. So you will be givin a Matlab function with about 100 lines of code that do the detrending
• Smoothing Standard Moving Average Smoothing and Kalman Filter are used to smooth raw measurements.
You will be given data with raw measurements as inputs to the algorithm and the expected output. The final Java algorithm must output the same output of the Matlab results.
