Convolution is a fundamental mathematical operation that describes how the shape of one function is modified by another. This simulator visualizes the convolution of two rectangular pulses, f(t) and g(t), producing a third function (f∗g)(τ). The core operation is defined by the convolution integral: (f∗g)(τ) = ∫_{-∞}^{∞} f(t) g(τ - t) dt. Here, τ is the shift parameter; as you slide one pulse past the other, the integral calculates the area of their overlap at each shift position. The simulator simplifies the concept by using simple, symmetric rectangular pulses, making the geometric interpretation of overlap area clear. Students will observe that the convolution of two rectangles of widths A and B results in a trapezoidal (or triangular, if A=B) output pulse. The width of the resulting pulse is A+B, demonstrating how convolution spreads or broadens signals. By interacting with the visualization, learners move beyond the abstract integral to see convolution as a measure of shared presence, a concept critical to signal processing (filtering), probability (sum of independent random variables), and physics (system response to an input). The model assumes ideal, noiseless pulses and a one-dimensional, continuous-time framework, providing a clean foundation before tackling more complex functions or discrete systems.
Who it's for: Undergraduate students in engineering, physics, and mathematics courses covering signals and systems, linear systems, or integral transforms. It is also valuable for advanced high school students in project-based STEM programs.
Key terms
Convolution
Convolution Integral
Rectangular Pulse
Shift Parameter (τ)
Signal Processing
Overlap Integral
Linear Time-Invariant (LTI) Systems
Trapezoidal Function
How it works
Convolution measures how much two functions overlap when one is reversed and shifted. For equal-height boxes, the integral is the length of the intersection — a building block for smoothing and linear systems.
Frequently asked questions
Why does the convolution of two rectangles produce a trapezoid or triangle?
The output value at each shift τ is the area of overlap between the two pulses. As one pulse slides, the overlap area increases linearly until the pulses are fully aligned, then decreases linearly. This linear change in area creates the sloping sides of a trapezoid. If the pulses have equal width, the 'fully aligned' region is a single point, resulting in a triangle.
What is a real-world application of convolving rectangular pulses?
In signal processing, a rectangular pulse can model a brief on/off signal or a uniform data packet. Convolution with another rectangle models the effect of a simple averaging filter or a finite-duration integration window. For example, this operation smooths a signal, averaging out rapid fluctuations over a short time window.
What does the shift parameter τ actually represent?
The parameter τ represents the relative time delay between the two functions. In the integral, g(τ - t) is a time-reversed and shifted version of g(t). Varying τ slides this modified pulse across the stationary pulse f(t). The output (f∗g)(τ) is therefore a function of this delay, showing how the overlap area changes with shifting alignment.
What is a key limitation of this simplified model?
This model uses ideal, noiseless pulses with sharp edges. Real-world signals are rarely perfect rectangles and often contain noise. Furthermore, the visualization is for continuous-time convolution; digital signal processing uses discrete convolution, which sums products at sample points rather than integrating a continuous area.