horizontal communication
Communication is written for a specific purpose and audience; an example of communication that is meant to help consumers is product sensitization.
communication that was not directly meant to be communicated
promotion related to communication because without communication you cannot promote your product by simply presenting it and have your own idea on how to sell your product
the main object of communication is to convey the right message to the right person , i.e. to the person for whom it is meant.
Quantization range refers to the range of values that can be represented by a quantization process. In digital signal processing, quantization is the process of mapping input values to a discrete set of output values. The quantization range determines the precision and accuracy of the quantization process.
horizontal communication
Quantization can be broadly categorized into two main types: uniform and non-uniform quantization. Uniform quantization divides the input range into equal-sized intervals, making it simple and efficient for certain applications. Non-uniform quantization, on the other hand, allocates varying interval sizes, often used in scenarios where certain ranges of input values are more significant, such as in audio compression. Additionally, there are techniques like scalar quantization and vector quantization, which refer to the quantization of individual signals versus groups of signals, respectively.
Sampling Discritizes in time Quantization discritizes in amplitude
The ideal Quantization error is 2^N/Analog Voltage
one syllable LOL
Communication is written for a specific purpose and audience; an example of communication that is meant to help consumers is product sensitization.
There are two types of quantization .They are, 1. Truncation. 2.Round off.
Mid riser quantization is a type of quantization scheme used in analog-to-digital conversion where the input signal range is divided into equal intervals, with the quantization levels located at the midpoints of these intervals. This approach helps reduce quantization error by evenly distributing the error across the positive and negative parts of the signal range.
Quantization noise is a model of quantization error introduced by quantization in the analog-to-digital conversion(ADC) in telecommunication systems and signal processing.
communication that was not directly meant to be communicated
quantisation noise decrease and quantization density remain same.