Howtosignalprocessing
- What is the linear prediction equation?
- What is linear prediction in statistics?
- What is the predictor coefficient?
- What is LPC in wireless communication?
What is the linear prediction equation?
Linear regression is one of the most commonly used predictive modelling techniques.It is represented by an equation 𝑌 = 𝑎 + 𝑏𝑋 + 𝑒, where a is the intercept, b is the slope of the line and e is the error term. This equation can be used to predict the value of a target variable based on given predictor variable(s).
What is linear prediction in statistics?
Linear prediction is a mathematical operation where future values of a discrete-time signal are estimated as a linear function of previous samples. In digital signal processing, linear prediction is often called linear predictive coding (LPC) and can thus be viewed as a subset of filter theory.
What is the predictor coefficient?
The predictor coefficients are obtained from the autocorrelation coefficients and quantized using a relatively high-rate quantizer. If the coefficient values are to be quantized directly, we need to use at least 12 bits per coefficient [156].
What is LPC in wireless communication?
Linear predictive coding (LPC) is a method used mostly in audio signal processing and speech processing for representing the spectral envelope of a digital signal of speech in compressed form, using the information of a linear predictive model.
