Programmer Group

1, Introduction to DTMF 1 meaning Dual Tone Multi Frequency DTMF (Dual Tone Multi Frequency) is composed of high-frequency group and low-frequency group, and the high-frequency group and low-frequency group each contain four frequencies. A high-frequency signal and a low-frequency signal are superimposed to form a combined signal, representing ...

1, Case introduction 1 application background The traditional desktop function signal generator has the disadvantages of huge volume, inflexible interface, fixed waveform and high price. In view of this current situation, a simple digital signal generator is completed according to the homework assigned by the teacher, which can produce white n ...

In any Automatic speech recognition system, the first step is to extract the features. In other words, we need to extract the identifiable components of the audio signal and throw away other messy information, such as background noise, mood, etc. Understanding how speech is produced is very helpful for us to understand speech. People pro ...

1 Introduction 1 origin and development of ant colony algorithm (ACA) In the process of studying the new algorithm, Marco Dorigo and others found that when ant colony is looking for food, they can exchange foraging information by secreting a biological hormone called pheromone, so they can quickly find the target. Therefore, in their doctoral ...

1 Introduction to algorithm 1.1 principle of BP neural network algorithm affected by relevant indexes As shown in Figure 1, when training BP using MATLAB's newff function, it can be seen that most cases are three-layer neural networks (i.e. input layer, hidden layer and output layer). Here to help understand the principle of neural network: 1 ...

1, Introduction EMG signal is easy to collect, but it is very difficult to understand and interpret the collected EMG signal. The analysis of EMG signals can enable us to understand the mechanism of force generation in muscles and how muscles produce movement. However, how to extract this information depends on the appropriate signal acquisiti ...

1, Introduction to cellular automata Development of cellular automata The original cellular automata was proposed by von Neumann in the 1950s to simulate the self replication of biological cells, but it has not been paid attention to by the academic community In 1970, after John Horton Conway of Cambridge University designed a computer game &q ...

1, Introduction to cellular automata Development of cellular automata The original cellular automata was proposed by von Neumann in the 1950s to simulate the self replication of biological cells, but it has not been paid attention to by the academic community In 1970, after John Horton Conway of Cambridge University designed a computer game &q ...

1. Introduction to Sparse Representation 1 Sparse Representation Theory Sparse means that most or all of the original signals are represented by a linear combination of fewer basic signals. After sparse representation, the more sparse the signal is, the more accurate the reconstructed signal will be. Set x< Rn as the signal to be processed ...

1. Introduction to cellular automata Development of 1-cell automata The original cellular automata was proposed by Von Neumann in the 1950s to mimic the self-replication of biological cells.But it has not been taken seriously by the academia. It was only after John Horton Conway of the University of Cambridge designed a computer game called &q ...