Pseudorandom sequence

Fig. 4, Gate function of a pseudorandom sequence of slots and bars and a schematic intensity distribution.

T. Richards, Graphical Representation of Pseudorandom Sequences, Computers and Graphics, 13(2) (1989) 261-262. 

Glowers, B.H., Belov, M.E., Prior, D.C., Danielson, W.F., Ibrahim, Y., Smith, R.D., Pseudorandom sequence modifications for ion mobility orthogonal time-of-flight mass spectrometry. Anal. Chem. 2008, 80, 2464. 

The remaining two chapters offer somewhat different approaches. Chapter 15 (Smith) details various possible pseudorandom sequences as spectral sources over the frequency range used for a.c. polarography, and gives several applications of this quite new technique. The final Chapter 16 (McCreery Rossi) describes a new FT technique which was first published (by those authors) this year (1981), in which Fourier transformation of the pattern of light diffracted near the edge of an electrode is used to discover the concentration profile of electroactive species very near to the electrode. 

Such a solution similar to Fig. 33c has been in use in the Southampton University, UK [7]. Excitation signal used in [7] is a pseudorandom sequence of binary pulses - the maximum length sequence MLS, see Fig. 27, enabling to perform fast and wide band impedance spectroscopy. The response signal is processed using a... 

Code synchronization Spread spectrum transmitters and receivers must synchronously generate identical pseudorandom sequences. Code synchronization is the act of bringing these two generators into alignment. 

A random sequence generator starts from a seed and produces a new Sequence of output bits whenever it receives a clock pulse. It is only a pseudorandom sequence however, as the same seed will always produce the same following sequence. 

To combat die problem of the same seed always generating the same pseudorandom sequence, the design in Figure 7.16b can be loaded with a new seed. Externally, the structure looks identical to the drcuit in Figure 7.16a The key difference in this case is that the output ports for the bit pattern are now bidirectional as they are used to load the new seed. This has significant consequences for fhe way in which these ports are designed as the drcuit cannot drive the external lines when a new seed is being loaded. 

The ALU consists of two elements - the adder and the pseudorandom sequence generator. In this design both these elements are present at the top level shown in Figure 8.11. An alternative approach woidd have been to use components. 

A very popular sequence of inputs is the pseudorandom binary sequence (PRBS). It is easy to generate and has some attractive statistical properties. See System Identification For Self-Adaptive Control, W. D. T. Davies, London, Wiley-Iflterscience, 1970. 

A further improvement in transmitted intensity can be achieved in the time-of-flight method by chopping the product beam in a pseudorandom modulation sequence. In this cross-correlation method, the detected signals are then decoded to yield the time-of-flight spectrum and thence the velocity distribution [112]. 

Fig. 4. Realization of bond percolation on a 50 X 60 section of the square lattice for four different values of q. The diagrams have been created using the same sequence of pseudorandom numbers, with the result that each graph is a subgraph of the next. Attentive readers may verify that open paths exist joining the left to the right side when = 0.51 but not at q = 0.49. (From Ref. 13, with permission.) continued)...

The random generator seed completely determines the sequence of the pseudorandom numbers that will be used for random events in simulations. Depending on the platform the sofiware is used on, the random generator seed may be set globally. This has to be taken into account when running simulation simultaneously. 

An important feature of most simulation languages is that they permit control of the pseudorandom numbers through random number streams or seeds, which permit the user to access different, and thus apparently independent, portions of the pseudorandom number sequence. Such control allows the user to induce dependence where desired or obtain independence where necessary. 

A pseudorandom number generator is a function that takes a short random seed and outputs a longer bit sequence that appears random. To be cryptographically secure, the output of a pseudorandom number generator should be computationally indistinguishable from a random string. In particular, given a short prefix of the sequence, it should be computationally infeasible to predict the rest of the se-... 

Signals for programming a controlling potential or current in an electrochemical cell include large amphtude potential sweeps or steps (as in cychc voltammetry or chronoamperometry), sine and square waves, pulse sequences, pseudorandom... 

A binary pseudorandom, excitation is the simplest to generate signal [7]. It can be formed directly from a clock signal with frequency /elk using the sequence of k trigger circuits (oo to flk i) constituting a shift register... 

The feature that separates Monte Carlo methodology from deterministic methods is mainly the use of random numbers or pseudorandom number sequences in the algorithm. The use of random number differs in the various Monte Carlo methods. A simple Monte Carlo method can be programmed in a few lines of coding or by using existing software, while a general-purpose routine can be quite complicated. 

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