Which decoding method is used for Viterbi algorithm?
Viterbi algorithm is utilized to decode the convolutional codes. Again the decoding can be done in two approaches. One approach is called hard decision decoding which uses Hamming distance as a metric to perform the decoding operation, whereas, the soft decision decoding uses Euclidean distance as a metric.
Which one is the most common decoding algorithm for Hmms?
The Viterbi algorithm
The Viterbi algorithm finds the most probable path through the HMM for a given sequence.
Why Viterbi decoding is efficient?
It is widely used in communication and signal processing to achieve low-error-rate data transmission. The Viterbi decoding method uses the maximum likelihood decoding (MLD) algorithm, which finds the most likely pattern from the received data, and is known as the optimum decoding method [1].
What is meant by Viterbi decoding?
A decoding algorithm developed in the late 1960s by Andrew Viterbi that is used to decode a particular convolutional code. Viterbi decoders have been the most effective way to decode wireless voice communications in satellite and cellphone transmissions.
What is the output of Viterbi algorithm?
Viterbi (2009), Scholarpedia, 4(1):6246. The Viterbi Algorithm produces the maximum likelihood estimates of the successive states of a finite-state machine (FSM) from the sequence of its outputs which have been corrupted by successively independent interference terms.
Is Viterbi a greedy algorithm?
The Viterbi algorithm is not a greedy algorithm. It performs a global optimisation and guarantees to find the most likely state sequence, by exploring all possible state sequences. An example of a greedy algorithm is the one for training a CART.
What is the difference between HMM and Viterbi?
For instance if your HMM task is to predict sunny vs. rainy weather for each day, Forward Backward would tell you the probability of it being “sunny” for each day, Viterbi would give the most likely sequence of sunny/rainy days, and the probability of this sequence.
Why is Viterbi algorithm important?
The Viterbi algorithm provides an efficient way of finding the most likely state sequence in the maximum a posteriori probability sense of a process assumed to be a finite-state discrete-time Markov process. Such processes can be subsumed under the general statistical framework of compound decision theory.
What is traceback depth in Viterbi decoder?
Description. The Viterbi Decoder block decodes convolutionally encoded data using a RAM-based traceback implementation. The Traceback depth is 32 . The block returns the first decoded output data sample after 148 clock cycles. The decoding latency is 4×Traceback depth + Constraint length + 13 valid input cycles.
What is Viterbi equalizer?
The MLSE Equalizer block uses the Viterbi algorithm to equalize a linearly modulated signal through a dispersive channel. The block processes input frames and outputs the maximum likelihood sequence estimate (MLSE) of the signal, using an estimate of the channel modeled as a finite input response (FIR) filter.