Ramatha's Random Ramblings

Studies have shown that the riskiest driving behaviour reported in the first half of 2020 are : device distractions from cellphone usage smoking (lighting a cigarette while driving) eating and drinking behind the wheel (food and drink consumption while driving)  drivers not using seat belts  anticipation (moments of late response to a situation) Pho to:  By Conn Hastings Data on the most widespread risky behaviours for delivery drivers attained that there is a tendency related to distracted driving were still leading factor among other dangerous habits, according to a report compiled by Lytx and Nexyad. Another risk factor identified by the Nexyad driving behaviour engine is the unstructured and slight differences to our current road infrastructure. The Nexyad engine takes into account the shape of roads, and map attributes including  Points Of Interest (POIs), intersections and road curvature (winding road, school zone, pedestrian crossing, railway, etc.). The riskiest

The Algorithms for  Viterbi Decoding The Viterbi decoder itself is the primary focus of this blog. The single most important concept to aid in understanding the Viterbi algorithm is the trellis diagram. The figure below shows the trellis diagram for our example rate 1/2 K = 3 convolutional encoder, for a 15-bit message. Trellis diagram for rate 1/2 K = 3 convolutional encoder, for a 15-bit message The four possible states of the encoder are depicted as four rows of horizontal dots. There is one column of four dots for the initial state of the encoder and one for each time instant during the message. For a 15-bit message with two encoder memory flushing bits, there are 17 time instants in addition to t = 0, which represents the initial condition of the encoder. The solid lines connecting dots in the diagram represent state transitions when the input bit is a one. The dotted lines represent state transitions when the input bit is a zero. Notice the correspondence betw